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Excel analytic solver and data mining

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I need to make sure whoever is assigned to this task has ASP analytic solver, data mining etc. and will be able to do all the excel assignments and have the added plug ins software program installed in their excel as a plug in so that this assignment is done correctly and there is no issue with the ASP plug in because my professor gave us a "free trial" and it won't work for anyone in class to install and hes still making us do it or figure it out which all 30 of us can't download it...so this is very important that someone already has this installed so it isn't an issue .All the instructions are in the Module 7 prompt and please make sure to label everything correctly for the file so " module 7 salmon stores, Module 7 credit score, module 7 blue or red"
Additional Instructions:
Data Undecided Age HomeOwner Female Married HouseholdSize Income Education Church 1 51 1 1 1 4 171.0 15 0 Best k? 1 37 1 1 1 3 96.0 18 0 1 53 1 1 1 6 86.0 20 0 Output Error Rate 0 33 1 1 1 2 176.0 18 1 0 46 1 1 1 6 420.0 15 1 Last Useful Decile 1 34 1 1 1 6 109.0 15 0 0 61 1 0 1 3 39.0 20 1 1 55 1 0 1 6 132.0 16 0 0 35 1 1 1 5 92.0 18 1 1 49 1 1 1 3 27.0 16 0 0 50 1 0 1 4 18.0 8 0 1 49 1 1 1 2 66.0 15 1 1 48 1 1 1 6 50.0 12 1 1 37 1 0 1 7 139.0 15 1 1 56 1 1 1 5 127.0 13 1 1 30 1 1 1 7 79.0 15 1 0 63 1 0 1 3 85.0 20 0 0 54 0 1 1 5 122.0 12 0 0 51 1 1 0 1 30.0 20 1 0 45 1 1 1 5 83.0 18 1 0 34 1 0 1 3 289.0 15 0 1 41 1 0 0 4 74.0 15 0 0 49 1 1 1 3 222.0 20 1 1 56 1 0 1 3 73.0 16 0 0 41 1 1 1 5 161.0 9 1 0 59 1 1 1 4 71.0 20 1 0 61 1 0 0 2 122.0 20 0 0 38 0 1 1 3 242.0 18 1 0 52 1 0 1 3 276.0 15 0 1 49 1 1 1 4 104.0 18 0 0 45 1 1 1 3 148.0 20 1 0 47 1 1 1 3 130.0 20 1 1 57 1 1 1 2 94.0 15 0 0 51 0 1 1 7 59.0 10 0 0 66 1 1 1 4 163.0 20 1 0 52 1 1 1 5 153.0 12 0 1 54 1 1 1 5 99.0 18 0 1 53 1 1 1 3 43.0 18 0 0 57 1 0 1 3 80.0 20 1 0 48 1 1 1 5 141.0 12 0 1 48 1 1 1 3 104.0 18 0 0 63 1 1 0 3 174.0 20 1 1 49 1 1 0 3 56.0 16 1 0 36 0 0 1 4 107.0 18 0 1 62 1 0 0 2 136.0 16 0 1 60 1 1 1 3 87.0 16 0 0 37 1 0 1 2 198.5 9 1 0 67 1 1 1 3 18.0 8 0 1 54 1 1 0 1 53.0 20 0 1 61 1 1 0 1 87.0 20 0 1 38 1 1 1 5 117.0 18 0 0 45 1 1 1 4 12.0 18 1 0 62 1 0 0 1 145.0 20 1 1 56 1 1 1 3 80.0 20 0 1 65 1 1 1 3 21.0 20 0 1 51 1 1 1 3 53.0 16 0 0 35 1 1 1 3 78.0 18 1 1 54 1 1 1 3 109.0 20 0 1 38 1 1 0 3 40.5 15 0 1 63 1 1 1 3 90.0 20 0 1 52 0 1 0 4 53.0 16 1 1 32 1 0 1 4 75.0 18 0 1 36 1 1 1 4 173.0 15 1 0 58 1 0 1 2 79.0 20 1 0 52 1 1 1 5 172.0 18 1 0 43 1 0 1 2 90.0 9 0 0 49 1 1 0 1 114.0 9 0 0 38 0 1 1 5 354.0 15 0 0 37 1 0 0 1 15.0 18 1 0 54 0 0 0 1 48.0 8 0 0 53 1 0 1 4 227.0 18 0 0 28 1 1 1 3 72.0 8 0 0 58 1 1 1 4 77.0 20 1 0 49 1 1 1 5 490.0 15 0 1 38 1 1 1 3 119.0 18 0 0 53 1 1 0 4 106.0 18 1 0 32 1 0 1 5 46.0 8 0 1 57 1 1 0 1 65.0 20 0 0 65 0 0 1 4 137.0 20 1 1 53 1 1 1 7 134.0 15 1 0 57 1 1 1 2 139.0 12 1 1 57 1 1 1 3 4.0 20 0 0 37 1 0 1 3 62.0 8 0 0 50 1 1 1 3 101.0 20 1 1 46 0 0 1 4 50.0 16 1 1 43 1 1 0 2 37.0 18 0 0 52 1 1 1 2 142.0 20 1 0 45 1 1 1 4 323.0 15 0 1 55 1 1 1 5 26.0 16 1 1 59 1 1 1 2 113.0 13 0 1 34 1 0 1 5 66.0 15 0 0 50 1 1 0 3 41.0 20 1 1 49 1 1 1 5 73.0 20 0 1 45 1 1 1 4 119.0 12 1 0 64 1 1 1 3 103.0 8 0 0 46 1 1 1 3 113.0 20 1 1 50 1 1 1 3 58.0 15 1 0 35 1 1 1 5 174.0 18 1 0 39 1 1 1 5 99.0 12 0 0 49 1 1 1 5 66.0 20 1 1 40 1 1 1 5 108.0 15 0 0 62 1 1 1 2 110.0 20 1 0 40 1 1 0 2 24.0 9 1 1 56 1 1 1 4 21.0 18 0 0 44 1 0 1 2 417.0 18 0 1 64 1 1 1 5 73.0 20 0 1 46 1 1 1 3 204.0 18 0 1 54 1 1 1 2 218.0 18 1 0 37 0 0 1 2 114.0 18 1 1 48 1 1 1 2 49.0 15 1 1 44 1 1 0 2 47.0 20 0 0 65 0 1 1 5 32.0 8 0 0 39 1 1 1 3 167.0 18 1 0 49 1 1 1 4 216.0 12 0 1 39 1 1 1 4 84.0 15 1 1 54 1 1 0 2 136.0 18 0 0 46 1 1 1 3 63.0 9 0 0 56 1 1 1 2 88.0 20 1 0 54 1 0 1 2 82.0 9 0 0 48 1 1 0 1 68.0 10 0 0 65 1 1 0 1 111.0 20 1 0 54 1 1 1 2 47.0 8 1 1 42 1 1 1 3 138.0 15 1 0 45 0 1 1 3 96.0 8 1 0 49 1 1 1 4 167.0 20 1 1 38 1 1 1 5 160.0 15 1 0 41 1 1 1 4 75.0 12 1 1 51 1 1 0 1 92.0 18 0 1 73 0 1 1 2 90.0 20 0 1 37 1 0 1 3 136.0 15 0 1 58 1 1 0 1 75.0 20 0 1 65 1 1 1 4 171.0 20 0 1 47 1 1 1 5 96.0 15 0 0 33 1 1 1 4 81.0 8 0 0 49 1 0 1 6 111.0 12 1 0 44 1 0 1 7 135.0 20 0 0 47 1 1 1 5 234.0 12 1 1 57 1 1 0 1 40.0 13 0 0 50 1 0 1 4 62.0 20 1 1 40 1 1 1 6 78.0 15 1 0 45 1 0 1 6 190.0 16 0 1 51 1 1 1 4 150.0 18 0 1 38 1 1 1 4 130.0 15 0 0 44 1 1 0 1 113.0 20 1 0 49 1 1 1 4 247.0 8 1 1 38 1 1 1 3 131.0 18 0 0 55 1 0 1 4 61.0 18 1 0 43 1 1 1 4 119.0 20 1 1 55 1 1 1 5 176.0 18 0 0 55 1 1 1 3 78.5 20 1 0 54 1 0 0 1 99.0 18 0 1 48 1 1 1 6 88.0 18 0 0 43 0 0 0 1 24.0 8 1 1 43 1 0 1 5 18.0 13 1 1 58 0 1 1 4 83.0 20 0 0 59 1 0 0 3 71.0 20 0 1 51 1 1 1 3 164.0 13 1 0 74 1 1 1 3 99.0 20 1 1 55 1 1 1 5 51.0 20 0 1 31 1 0 1 6 151.0 15 0 1 51 1 1 1 3 127.0 18 0 1 44 1 1 1 3 94.0 15 1 0 52 1 1 1 4 190.0 10 1 0 54 1 1 1 3 92.0 20 1 0 66 1 0 1 2 68.0 20 0 0 48 0 0 1 3 85.0 20 0 0 54 1 0 1 4 126.0 18 1 1 48 1 1 1 5 127.0 18 0 1 64 1 0 1 3 100.0 16 0 0 76 1 0 1 3 22.0 20 0 1 62 0 1 0 3 65.5 20 0 0 54 0 1 1 4 107.5 18 1 0 53 1 1 1 6 214.0 18 1 1 39 1 0 1 4 91.0 15 0 0 46 1 0 1 6 77.0 8 1 0 69 0 0 1 4 85.5 10 0 0 53 1 0 1 2 85.0 20 1 1 39 1 1 1 4 118.0 15 1 1 43 1 1 1 4 233.0 18 0 0 61 1 1 0 3 17.0 20 1 0 66 1 1 0 2 38.0 20 1 0 44 1 1 1 3 157.0 12 1 0 52 0 1 0 1 69.0 20 1 1 45 1 1 1 5 61.0 20 0 0 60 1 0 1 2 134.0 20 0 1 37 1 1 1 3 161.0 18 0 0 47 1 1 1 3 101.0 12 1 0 46 0 1 1 4 123.0 18 1 1 46 1 1 0 1 85.0 18 0 1 61 1 1 1 5 108.0 20 0 1 51 1 1 1 2 60.0 18 0 0 41 1 1 1 4 99.0 18 1 1 57 1 1 1 5 87.0 16 0 0 47 1 0 0 1 94.0 20 0 1 43 1 1 1 3 73.0 15 1 0 50 1 1 1 3 44.0 18 1 0 35 1 0 1 3 90.0 18 1 0 39 1 0 0 1 55.5 8 0 0 53 1 1 1 5 24.0 18 1 0 52 1 1 1 4 57.0 8 0 0 55 1 0 1 4 237.0 20 0 0 56 1 0 1 4 56.0 20 1 0 58 1 0 1 2 55.0 8 1 0 48 1 0 0 1 163.0 20 1 0 69 1 1 1 2 30.0 20 1 1 52 1 1 1 4 150.0 20 0 1 54 1 0 1 2 63.0 13 0 1 42 1 1 0 1 108.0 15 0 0 33 1 1 1 2 111.5 8 0 1 37 0 1 1 4 107.0 15 0 1 51 1 1 1 3 82.0 20 0 1 36 1 0 1 3 160.0 15 1 1 53 1 1 0 1 9.0 20 0 1 51 1 0 1 4 56.0 16 1 1 46 1 1 1 2 96.0 18 0 0 48 1 1 1 2 140.0 20 1 0 39 1 1 0 4 31.0 18 1 1 46 1 1 1 2 67.0 20 0 1 64 1 1 1 3 16.0 13 0 0 53 1 1 1 5 124.0 8 1 1 47 1 1 1 4 103.0 18 0 1 57 1 0 1 3 108.0 13 1 0 52 0 0 0 1 132.0 8 1 1 43 1 1 1 2 70.0 18 0 1 49 1 1 1 4 222.0 20 0 0 51 0 1 0 1 131.5 18 1 0 41 0 1 1 2 108.0 18 1 1 62 1 1 1 2 61.0 20 0 0 57 1 1 0 1 7.0 8 1 1 46 1 1 0 1 82.0 18 0 0 31 1 0 1 4 135.0 18 1 0 61 1 0 1 3 77.0 20 1 0 40 1 1 1 3 135.0 18 1 0 47 1 0 1 4 132.0 12 0 0 37 1 1 1 4 170.0 18 1 1 47 1 1 1 4 163.0 13 0 0 54 1 1 1 6 147.0 12 1 1 47 1 1 1 5 92.0 13 1 1 36 1 1 1 7 60.0 15 1 1 49 1 0 1 4 138.0 16 1 0 63 1 1 1 5 450.0 20 1 1 37 1 0 1 3 20.0 12 1 0 61 0 0 1 3 95.0 20 0 0 41 1 1 0 2 22.0 10 1 0 48 1 1 1 2 64.0 20 1 0 54 1 0 1 3 110.5 8 1 1 46 1 1 1 3 101.0 18 0 0 46 1 1 1 2 62.0 9 0 0 46 0 1 0 1 135.5 8 0 0 47 1 0 1 3 177.0 20 1 0 50 1 0 1 4 97.0 20 0 0 37 1 0 1 4 58.0 18 1 1 61 1 1 1 2 59.0 20 1 1 61 1 0 1 6 12.0 16 1 0 44 0 1 1 5 202.0 18 1 1 42 0 1 1 5 59.0 18 0 0 38 1 0 1 3 141.0 18 0 0 40 1 1 1 4 56.0 18 1 0 69 1 1 1 2 99.0 20 1 0 43 0 1 1 5 136.0 8 0 1 35 1 1 1 6 28.0 15 0 0 49 1 1 1 2 117.0 12 1 1 58 1 1 1 2 112.0 20 0 0 57 1 1 1 2 108.0 8 1 1 62 0 1 0 2 10.0 8 1 0 45 1 1 1 2 98.0 18 1 1 33 1 1 1 3 21.0 18 1 1 68 1 0 1 5 120.0 16 1 0 43 1 1 1 6 77.0 12 0 0 44 1 1 0 5 79.5 18 1 0 70 1 0 1 3 41.0 20 1 1 58 0 1 1 3 16.0 16 0 0 53 1 0 1 2 68.0 20 0 1 43 1 1 1 6 119.0 15 1 0 59 1 0 1 2 80.0 20 1 0 56 1 1 1 6 101.0 12 0 0 43 1 1 1 4 85.0 20 1 0 51 0 0 1 3 107.0 9 0 1 73 1 1 1 3 64.0 16 0 0 54 0 0 1 3 49.0 8 0 0 43 0 1 1 2 107.0 20 1 1 49 1 1 1 4 154.0 15 1 1 51 1 0 1 6 159.0 16 1 0 52 1 0 0 1 66.0 20 0 1 47 1 1 0 1 34.0 20 0 1 45 1 1 0 1 5.0 18 0 0 75 1 1 0 1 67.0 20 1 0 43 1 1 1 5 87.0 8 0 1 32 1 1 1 3 37.0 15 0 1 64 1 1 1 4 75.0 20 0 1 70 1 1 0 1 115.0 20 0 0 52 1 1 1 2 69.5 20 1 0 52 1 0 1 3 43.0 10 0 0 48 1 0 1 3 90.0 20 0 0 51 1 1 1 2 155.0 18 1 0 70 0 1 0 1 98.0 8 1 0 34 1 1 1 3 4.0 18 1 1 34 1 0 1 3 126.0 15 0 1 53 1 1 1 5 56.0 15 1 1 31 1 0 1 5 108.0 15 1 0 43 1 1 1 3 94.0 18 1 0 50 1 0 0 2 118.0 20 1 0 46 1 0 1 5 153.0 18 1 1 64 1 0 1 4 142.0 20 0 1 59 1 1 1 4 40.0 20 0 0 42 1 1 1 4 196.0 18 1 1 37 1 0 1 5 48.0 15 1 1 49 0 1 1 3 112.0 13 0 0 46 1 1 0 1 366.0 18 1 1 60 0 1 1 2 113.0 20 0 0 54 1 1 1 4 46.0 18 1 0 40 1 1 1 6 270.0 15 0 0 50 1 0 1 4 152.0 18 1 1 31 1 0 1 5 136.0 15 1 0 45 1 1 1 3 134.0 18 1 0 65 1 1 0 4 58.0 8 0 0 36 1 1 1 5 91.0 18 1 0 42 1 1 1 6 239.0 12 0 0 35 0 1 1 6 152.0 12 1 1 58 1 1 1 3 88.0 20 0 0 37 1 1 1 5 142.0 18 1 0 49 0 0 1 7 117.0 8 0 0 34 1 1 1 4 94.0 12 0 0 35 1 1 1 6 229.0 15 1 0 54 1 1 1 2 32.0 20 1 0 42 1 1 0 1 216.0 18 1 1 48 1 1 0 1 61.0 18 0 1 31 1 1 1 4 109.0 15 1 1 57 1 1 1 2 50.0 16 1 0 55 0 0 1 5 37.5 8 1 1 36 1 1 1 6 142.0 15 1 1 47 1 0 0 2 31.0 18 1 0 45 1 0 1 3 258.0 8 0 1 29 1 1 1 7 131.0 15 0 1 68 1 1 1 4 63.0 16 0 0 59 1 1 0 1 41.0 20 1 0 42 1 1 0 3 48.0 18 1 0 61 1 0 1 3 127.0 20 0 0 59 1 0 1 4 219.0 16 1 1 44 1 0 0 1 59.0 18 1 1 41 1 0 1 3 70.0 15 0 0 43 1 1 1 3 260.0 20 1 1 55 1 1 1 2 178.0 18 0 0 43 0 1 0 1 25.0 8 0 1 45 0 1 1 3 6.0 20 0 1 62 1 1 0 1 131.0 20 0 0 46 1 1 1 6 205.0 12 0 0 61 1 1 1 3 26.0 20 1 1 47 1 1 1 7 165.0 15 1 0 47 1 1 0 2 113.0 18 1 0 53 1 1 1 5 220.0 20 1 0 44 1 1 1 2 235.0 8 1 0 45 1 1 0 4 11.0 18 1 1 69 1 1 1 3 218.0 20 0 0 46 1 1 1 4 187.0 12 1 1 37 1 1 1 2 81.5 15 0 1 57 1 1 1 3 68.5 15 0 1 50 1 1 1 2 83.0 15 1 0 51 1 1 1 5 539.0 18 1 0 41 1 1 0 1 491.0 18 1 0 34 1 1 1 4 290.0 15 0 1 69 1 1 0 2 50.0 20 0 0 30 1 1 1 6 291.0 15 0 1 48 0 1 1 2 210.0 20 0 0 60 1 1 0 2 75.0 20 1 0 58 1 1 0 1 107.5 8 1 0 55 1 1 1 6 107.0 20 1 1 30 1 0 1 2 158.0 15 0 0 30 1 1 1 5 504.0 15 0 0 53 1 0 1 2 159.0 10 0 0 45 1 0 1 3 179.0 16 0 1 42 1 1 0 1 64.0 20 0 1 58 1 1 1 6 18.0 15 1 1 34 1 1 1 6 173.0 15 1 0 54 1 1 0 1 48.0 18 1 1 62 1 1 0 1 30.0 20 0 0 32 1 1 1 4 424.0 15 0 0 36 1 1 1 4 127.0 18 1 0 49 1 1 1 4 45.5 18 1 0 34 1 1 1 2 256.0 15 0 1 37 1 1 1 5 17.0 15 0 0 44 1 1 1 4 130.0 12 0 1 60 1 1 1 2 102.0 20 0 1 41 1 0 1 4 56.0 15 1 0 43 1 0 1 3 131.0 12 1 0 51 0 0 1 2 58.0 18 1 0 50 0 0 1 2 47.0 8 1 0 63 1 1 1 2 110.0 20 1 0 32 0 0 1 3 187.0 12 0 0 36 1 1 0 1 94.0 9 0 0 48 1 1 0 1 44.0 18 1 1 55 1 1 1 5 52.0 20 0 1 47 1 1 1 6 17.0 15 0 0 47 1 1 1 4 88.5 20 1 0 34 1 0 1 4 175.0 15 0 0 43 1 1 1 4 38.0 8 1 1 47 1 1 1 3 137.0 18 0 0 32 1 1 1 5 96.0 8 0 1 48 1 1 1 4 144.0 18 0 1 41 1 1 1 6 132.0 15 0 0 63 1 0 1 4 22.0 8 1 0 40 1 0 0 3 60.0 8 0 0 49 1 1 1 3 124.0 18 1 1 43 1 1 1 3 21.0 18 0 1 62 0 1 0 1 44.0 20 0 0 68 1 0 1 3 122.0 20 1 0 52 1 1 1 4 24.0 10 0 0 41 0 1 0 3 26.0 8 0 0 54 1 0 0 1 111.0 20 1 1 44 1 1 1 6 67.0 15 0 0 58 1 0 1 5 344.0 16 0 1 64 1 1 1 2 120.0 20 0 0 47 1 1 0 2 48.0 18 1 0 28 1 1 1 7 82.0 12 1 0 35 1 0 1 4 189.0 18 0 1 51 1 1 1 2 56.0 20 0 1 50 1 1 0 1 85.5 15 1 0 43 0 1 0 6 22.0 10 1 0 53 1 1 1 2 47.0 10 0 1 49 1 1 1 4 171.0 20 0 0 42 1 1 0 3 57.0 12 0 0 45 1 1 1 5 184.0 9 1 0 45 1 1 1 4 183.0 15 1 0 47 1 1 0 1 491.0 15 0 0 48 1 1 1 2 64.0 20 1 1 48 1 1 1 3 182.0 20 0 0 56 1 0 1 2 62.0 20 0 1 59 1 1 1 3 98.0 20 0 0 53 1 1 1 6 69.0 12 1 0 40 1 1 0 3 14.0 18 1 1 46 1 1 1 3 55.0 18 0 1 57 1 1 1 4 96.0 20 0 1 53 1 0 1 6 27.0 16 0 0 55 1 1 0 2 52.0 9 0 1 56 1 1 0 1 46.5 18 0 0 64 1 0 1 4 115.0 20 0 0 53 1 1 0 2 28.0 10 0 0 67 1 0 1 4 70.0 20 0 0 44 0 0 1 5 199.0 15 1 1 34 0 1 1 2 116.0 18 0 1 49 1 1 1 2 146.0 18 0 0 49 1 1 1 2 47.0 8 0 1 45 1 0 1 5 113.0 16 0 0 60 0 0 0 2 5.0 20 1 1 47 1 1 1 5 88.0 15 0 0 58 1 1 1 4 84.0 18 1 0 42 1 1 1 3 75.0 12 1 0 43 1 1 1 3 55.0 18 1 0 60 1 1 0 1 90.0 20 1 1 45 1 1 1 7 187.0 13 1 0 67 1 1 0 1 4.0 20 1 0 50 1 1 1 3 33.0 18 1 1 68 1 1 0 1 37.0 13 1 0 39 1 0 1 3 174.0 8 1 1 39 1 1 0 1 88.0 18 0 0 57 1 1 1 5 301.0 15 0 1 54 1 1 1 5 101.0 16 1 1 46 1 1 1 5 162.0 20 0 1 49 1 1 1 6 145.0 15 0 0 57 1 1 0 1 158.0 18 1 0 62 1 0 1 3 21.0 10 0 0 45 1 1 1 5 80.0 18 1 0 67 1 1 1 2 236.0 20 1 1 40 1 0 1 4 151.0 15 0 1 44 1 1 1 5 73.0 15 0 1 66 1 1 0 1 80.0 20 0 1 55 1 1 1 5 144.0 20 0 1 35 1 1 1 3 136.5 15 1 1 34 1 1 1 2 135.0 15 1 1 52 1 0 0 1 106.0 15 1 0 36 1 1 1 4 84.0 18 1 0 54 1 1 1 3 54.0 20 1 0 45 1 1 1 2 91.0 18 1 1 55 1 1 1 2 6.0 18 0 0 32 1 1 1 5 225.0 15 0 0 49 0 0 1 4 104.0 18 0 1 50 1 1 1 3 128.0 20 0 1 66 1 1 1 6 90.0 13 1 0 67 1 1 0 1 6.0 20 1 0 38 0 1 1 4 79.0 8 0 1 32 1 1 1 7 82.0 15 1 1 35 1 1 1 3 72.0 18 0 0 47 1 1 1 3 86.0 12 0 0 47 0 1 0 1 140.0 8 1 1 54 1 1 1 2 113.0 18 0 1 58 1 1 1 2 143.0 20 0 1 39 1 1 1 3 149.0 15 1 1 41 1 0 1 5 53.0 16 0 0 50 1 1 0 1 63.0 18 1 0 43 0 1 1 5 122.0 8 0 0 56 1 1 1 2 41.0 20 1 1 42 1 1 1 3 70.0 18 0 0 48 0 0 0 1 145.0 20 0 1 48 0 1 0 1 4.0 20 0 1 55 0 1 1 4 133.0 15 0 0 71 0 0 1 2 38.0 8 1 1 48 1 1 1 4 145.0 18 0 1 42 1 1 1 4 162.0 15 1 0 52 1 0 1 5 139.0 18 1 1 49 1 1 1 2 95.0 18 0 0 43 1 1 1 4 285.0 15 0 0 48 1 1 1 5 160.0 8 0 0 50 1 1 1 4 271.0 15 1 1 34 1 1 0 2 77.0 15 0 0 34 1 0 0 2 12.5 8 1 0 56 1 1 0 1 88.0 20 1 0 50 1 0 0 5 46.0 12 1 0 61 1 1 1 2 11.0 8 0 0 47 1 0 1 3 41.0 12 1 1 34 1 1 1 3 134.0 15 0 0 44 1 1 1 4 247.0 15 0 0 53 1 1 1 4 174.0 20 1 1 50 1 1 0 1 41.0 20 0 0 67 1 0 1 6 9.0 20 1 0 62 1 1 1 5 137.5 20 1 0 39 1 1 1 4 477.0 15 1 0 54 1 1 1 2 90.0 20 1 1 44 1 1 1 7 73.0 15 1 0 47 0 1 1 3 63.0 8 0 0 54 1 1 1 6 26.0 8 0 1 64 1 0 1 2 93.0 13 1 1 48 1 1 1 2 137.0 20 0 1 47 1 1 1 3 45.0 16 1 1 62 1 1 1 2 76.0 20 0 0 38 1 1 0 1 236.0 8 0 0 40 1 1 1 2 38.5 8 0 0 44 0 1 1 2 80.0 8 0 0 67 1 0 1 4 114.0 20 0 0 59 1 1 1 3 139.0 20 1 0 49 1 1 1 5 152.0 9 0 0 59 1 0 1 2 46.5 20 0 0 52 1 1 1 3 209.0 18 1 1 50 1 1 1 3 66.0 15 1 1 54 1 1 1 3 82.0 16 1 1 40 1 0 1 5 101.0 15 1 0 47 1 0 1 4 154.0 8 1 0 53 1 0 1 3 167.0 20 1 0 33 1 0 1 6 178.0 15 1 1 42 1 0 0 1 79.0 15 1 0 43 1 1 1 3 40.0 20 1 1 57 1 1 1 5 88.0 16 1 1 57 0 1 1 6 33.0 20 0 0 56 1 1 1 2 181.0 16 0 0 48 0 1 0 3 57.0 8 1 0 52 1 1 0 1 146.0 20 1 1 45 1 1 1 3 121.0 18 0 0 49 1 0 0 2 239.0 18 0 0 43 1 1 0 2 80.0 8 1 0 48 1 1 1 2 62.0 18 1 0 50 1 0 0 1 25.0 20 1 0 32 1 1 0 4 56.0 8 0 0 63 1 0 1 4 47.0 20 0 0 50 1 1 1 3 105.0 8 1 0 64 1 1 0 1 46.0 20 1 0 57 0 1 1 3 131.0 8 1 1 49 1 1 0 1 57.0 20 0 1 52 1 1 1 3 97.0 15 1 0 47 1 1 1 4 81.0 18 1 1 30 1 1 1 2 54.0 15 0 0 55 0 1 1 3 96.0 18 1 0 54 0 1 0 2 15.0 8 0 0 53 1 1 1 2 54.0 20 1 0 44 1 1 0 4 41.0 12 1 1 46 1 0 1 5 62.0 15 0 0 32 1 1 1 4 109.0 12 1 1 58 1 1 0 1 55.0 20 0 1 68 1 1 1 4 43.0 20 0 0 37 0 1 1 4 110.0 12 0 0 43 1 0 0 1 186.0 20 0 0 50 1 1 1 5 127.0 18 1 1 73 1 1 0 2 12.5 16 1 1 47 1 1 1 5 147.0 15 1 1 44 1 0 1 3 118.0 15 0 0 47 1 1 1 3 159.0 18 1 0 39 1 1 1 3 68.0 18 1 1 41 0 1 0 1 10.0 15 0 0 47 0 1 1 5 299.0 12 0 0 56 1 1 1 2 28.0 20 1 0 63 0 1 1 4 28.0 20 1 0 30 1 1 1 5 128.0 12 1 0 47 1 0 1 3 120.0 20 0 1 51 1 1 1 6 18.0 15 1 1 32 1 1 1 6 146.0 15 0 0 40 1 1 1 6 121.0 12 1 0 36 1 1 1 4 102.0 9 1 0 47 1 0 1 4 77.0 18 1 1 48 1 1 1 4 133.0 18 0 0 59 1 1 0 1 59.0 20 1 0 47 1 1 1 4 133.0 9 1 0 46 1 1 1 4 258.0 15 1 1 42 1 1 1 2 168.0 15 0 1 43 1 1 1 2 88.0 18 0 0 55 1 1 1 6 154.0 10 1 1 35 0 1 1 3 120.0 15 1 1 53 1 1 1 4 109.0 18 0 1 34 1 1 1 5 133.0 15 0 0 38 1 1 1 3 84.0 12 1 0 50 0 1 1 3 91.5 9 0 1 46 1 1 1 4 104.0 15 1 1 36 1 1 0 2 54.0 12 1 0 44 1 0 1 3 70.0 18 1 1 43 0 1 1 2 120.0 20 0 1 33 1 1 1 5 56.0 15 1 0 35 1 0 1 3 22.0 18 1 0 38 1 1 1 5 211.0 15 0 0 37 1 1 0 1 196.0 18 1 0 40 1 1 1 5 324.0 8 1 0 41 0 1 1 3 21.0 8 1 1 55 1 1 1 2 71.0 20 0 0 43 1 1 1 3 147.0 12 0 0 41 1 1 1 2 71.0 18 1 0 43 1 1 1 3 119.0 18 1 0 59 1 0 1 4 364.0 20 1 0 59 1 1 1 3 47.0 20 1 0 62 0 1 1 3 50.0 10 1 0 51 1 1 1 4 79.0 20 1 1 40 0 1 0 4 17.0 15 0 1 63 0 1 1 6 50.0 16 1 1 49 1 0 1 5 108.0 15 0 1 41 1 1 1 5 151.0 15 0 1 50 1 1 1 3 183.0 18 0 0 50 1 1 1 3 101.0 20 1 0 67 1 0 1 3 22.0 10 1 0 70 1 1 1 5 457.0 16 1 0 63 1 0 1 4 165.0 20 1 0 43 1 1 0 4 63.0 20 1 0 41 1 1 1 6 51.0 12 0 0 45 0 1 1 3 193.0 15 0 1 64 1 1 1 2 124.0 20 0 0 40 1 1 1 2 214.0 18 1 0 45 1 1 1 2 59.5 9 0 1 54 1 1 1 4 97.0 16 1 0 57 1 1 0 1 33.0 8 0 1 65 1 1 1 3 84.0 20 0 1 43 1 0 1 4 91.0 13 1 0 54 1 1 1 2 143.0 20 1 0 65 1 0 1 5 139.0 20 0 1 52 1 1 1 4 108.0 18 0 0 37 1 1 1 3 81.0 9 1 0 54 0 1 0 3 87.0 18 1 1 46 1 1 1 3 108.0 20 0 0 52 1 0 1 3 97.0 20 1 1 40 1 1 1 3 119.0 15 0 0 32 1 1 1 7 114.0 12 1 0 40 0 0 1 3 84.0 8 1 0 48 1 1 1 4 176.0 20 1 0 51 1 0 1 5 93.0 20 1 0 47 1 1 0 1 24.0 20 1 0 47 0 1 0 1 32.0 8 0 0 59 0 1 1 3 63.0 8 1 0 47 1 1 1 2 36.0 18 1 0 37 0 1 1 3 130.0 9 1 1 45 1 1 1 5 86.0 15 1 0 47 1 1 0 1 102.5 20 1 0 67 1 1 1 2 193.0 8 0 1 65 0 1 0 1 157.0 20 0 0 48 1 1 1 5 121.0 20 1 1 57 1 1 1 6 103.0 20 0 0 66 1 1 0 1 51.0 20 1 1 52 1 0 1 7 114.0 16 1 1 69 1 1 1 3 121.0 20 0 0 60 0 1 1 3 17.0 8 1 0 40 0 0 0 2 62.0 18 1 0 47 1 1 0 1 87.0 9 1 1 42 0 0 1 6 132.0 15 1 0 48 1 1 1 5 329.0 20 0 0 64 0 1 1 3 30.0 20 1 1 46 1 1 1 5 4.0 16 0 0 41 1 1 1 5 197.0 13 1 0 52 1 1 0 1 162.0 20 1 1 48 1 1 1 5 134.0 16 0 0 61 1 1 1 3 95.0 20 1 1 64 1 1 1 3 153.0 20 0 1 50 1 1 0 2 25.0 20 0 1 53 1 1 1 4 39.0 20 0 1 52 1 1 1 5 21.0 16 0 1 45 1 1 1 4 218.0 18 0 1 58 1 1 1 3 39.0 20 0 1 59 1 1 1 2 132.0 16 0 0 41 1 1 1 3 85.0 20 1 0 37 1 1 1 4 76.0 18 1 1 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0 0 2 72.0 18 1 0 57 1 0 0 2 12.0 8 0 0 31 1 1 1 6 309.0 8 1 0 53 1 1 1 5 97.0 18 1 1 76 1 1 1 4 76.0 20 0 0 45 1 1 1 4 81.0 9 1 0 37 1 1 1 4 110.0 8 1 1 43 0 0 1 5 111.0 15 1 1 51 1 1 1 2 92.0 20 0 1 45 1 1 1 3 90.0 15 0 0 52 1 1 1 5 233.0 15 1 1 40 0 1 1 6 115.0 18 0 1 45 1 1 1 6 72.0 15 1 1 46 0 1 1 4 96.0 16 1 1 56 1 1 1 2 112.0 20 0 1 69 1 1 1 2 30.0 8 1 0 50 1 1 1 4 226.0 18 1 0 56 1 1 1 4 72.0 12 0 1 50 1 1 0 1 107.0 18 0 1 57 1 1 0 2 127.0 13 0 0 50 0 1 1 3 197.0 18 1 0 58 1 0 1 4 42.0 20 0 0 62 0 1 1 2 26.0 20 1 1 43 1 1 1 6 76.0 16 1 0 42 1 0 1 3 54.0 18 0 1 54 1 1 1 3 26.0 20 0 1 43 0 1 1 3 93.0 15 1 0 64 0 1 0 1 11.0 10 0 0 46 1 0 1 2 46.0 20 0 0 68 1 1 1 3 162.0 20 1 0 54 0 1 1 2 116.0 12 1 1 34 1 1 0 1 56.0 15 0 1 38 0 1 1 3 203.0 18 0 1 50 1 0 1 2 56.0 8 0 1 41 0 1 1 5 120.0 18 0 0 50 0 0 1 3 157.5 8 0 0 55 1 1 1 4 57.5 20 1 0 49 1 1 0 4 55.0 18 1 0 42 0 1 0 1 22.0 8 0 1 57 1 1 1 3 148.0 20 0 1 46 1 1 1 3 30.0 20 0 1 44 1 1 0 1 62.0 18 0 0 49 0 1 1 3 34.0 18 1 0 49 1 1 1 3 75.0 20 1 1 53 0 1 1 3 87.0 13 0 1 45 1 1 1 4 39.0 20 0 1 55 1 1 1 5 100.0 18 0 0 49 1 1 1 4 21.0 8 1 1 63 1 1 1 3 179.0 20 0 1 59 1 1 1 6 135.0 16 1 0 58 1 0 1 4 62.0 18 1 1 46 1 1 1 2 81.0 15 1 0 67 0 1 1 3 24.0 20 1 1 60 1 1 1 4 73.0 20 0 0 58 1 0 0 2 27.0 18 0 0 54 1 1 0 1 90.0 20 1 1 59 1 1 0 1 123.0 13 1 0 56 0 1 0 1 50.0 20 1 0 53 1 0 1 2 39.0 20 1 1 47 1 1 0 1 17.0 18 0 0 51 1 1 1 2 99.0 20 1 1 39 1 1 1 6 130.0 15 1 0 60 1 1 1 5 160.0 20 1 1 40 0 1 1 4 115.0 15 0 0 66 0 1 1 2 49.0 20 1 1 76 1 0 1 4 150.0 16 1 1 74 1 1 1 3 40.0 20 0 0 52 1 1 1 4 103.0 10 1 0 47 1 0 1 7 28.0 12 1 1 62 1 1 0 6 72.0 16 0 1 58 1 1 1 3 109.0 20 0 0 43 1 1 1 3 23.0 9 0 1 60 1 1 1 3 93.0 20 0 1 56 1 1 0 3 128.0 18 0 1 35 1 1 0 1 203.0 18 0 0 35 1 1 0 1 110.0 12 1 0 38 1 1 1 3 171.0 18 1 0 53 0 1 1 6 90.0 20 1 0 49 1 1 1 4 489.0 15 0 1 49 1 1 0 1 111.0 18 0 1 68 1 1 1 3 126.0 20 0 0 64 1 0 1 2 144.0 20 0 0 48 1 1 1 5 241.0 18 1 1 44 1 1 0 3 37.0 18 0 1 31 1 1 1 3 73.0 15 1 0 69 1 1 1 3 53.0 20 1 0 61 1 1 0 2 9.0 8 0 0 33 1 1 0 2 73.0 12 0 0 59 1 1 1 4 39.0 20 1 1 63 1 1 1 3 169.0 20 0 1 61 1 0 1 4 88.0 13 0 0 49 1 1 1 3 60.0 18 1 0 39 0 1 1 2 61.0 8 0 1 61 1 1 0 1 40.0 20 0 0 32 1 1 1 3 92.0 12 1 0 41 1 1 1 3 60.0 18 1 0 67 1 1 1 4 48.0 20 1 1 52 1 1 1 7 90.0 15 1 1 43 1 1 0 1 25.0 18 0 0 35 0 1 1 5 29.0 12 0 0 47 1 0 1 3 70.0 20 0 1 72 1 1 0 3 27.0 20 0 0 47 1 1 0 3 25.0 9 1 1 64 1 1 1 2 7.0 20 0 0 51 1 1 1 3 515.0 18 0 0 46 1 1 1 3 451.0 18 0 0 58 1 1 0 6 111.0 20 1 1 59 0 1 0 3 136.5 13 1 0 50 1 1 1 2 64.0 12 0 1 63 1 1 1 3 76.0 20 0 0 34 1 1 0 2 80.5 18 1 1 53 1 1 1 6 169.0 15 0 1 55 1 1 1 4 137.0 13 1 0 42 1 1 1 5 483.0 18 0 1 51 1 0 1 5 131.0 13 0 0 43 1 1 1 4 130.0 18 1 0 42 1 1 1 3 128.0 20 1 1 58 0 1 1 5 139.0 16 1 0 47 1 1 1 2 87.0 8 0 0 35 1 1 1 5 313.0 15 0 1 52 0 1 1 2 100.0 20 0 0 68 1 1 0 1 58.0 20 1 0 70 1 1 0 1 129.0 10 0 1 64 1 1 1 3 6.0 20 0 0 44 1 1 1 5 85.0 18 1 0 74 1 1 1 4 6.0 20 1 0 50 1 1 1 7 80.0 18 1 1 48 1 1 1 5 185.0 20 0 0 32 1 0 1 5 169.0 18 0 1 53 1 1 1 4 111.0 15 1 1 38 1 1 0 5 23.0 15 1 0 50 1 1 1 6 264.0 15 1 1 49 1 1 1 2 209.0 18 0 0 45 1 1 1 2 58.0 8 0 0 49 1 0 1 3 144.0 12 0 1 56 1 0 1 3 93.0 13 1 0 35 1 0 1 7 549.0 15 0 1 43 1 1 1 5 141.0 15 1 1 60 1 1 1 6 64.0 16 1 0 32 1 1 0 4 35.0 8 1 1 34 1 1 1 2 137.0 15 0 0 36 1 0 0 1 116.0 18 1 1 70 1 1 0 1 72.0 13 0 1 70 1 1 1 3 104.0 20 0 1 58 1 1 1 2 104.0 13 1 1 57 0 1 0 1 64.0 15 0 0 51 1 1 1 5 142.0 18 1 0 78 1 1 0 1 54.0 8 1 0 45 0 1 0 2 15.0 8 1 1 51 1 1 1 3 100.0 15 1 0 53 0 1 1 5 205.0 15 1 0 39 1 1 1 2 146.0 18 1 1 30 0 1 1 3 40.0 15 1 1 47 0 1 1 5 168.0 20 0 1 43 1 0 1 5 69.0 15 1 0 43 1 1 1 5 41.0 12 0 0 49 1 1 0 1 118.5 12 1 1 42 1 1 1 4 34.0 20 0 0 35 1 1 1 3 77.0 18 1 1 55 1 1 1 3 67.5 16 0 0 73 1 1 1 5 40.0 20 1 1 69 1 1 1 2 67.0 20 0 0 56 1 1 0 3 68.0 20 1 0 53 1 1 0 1 42.0 10 1 1 52 0 1 0 2 55.0 20 0 0 59 1 0 1 2 124.0 20 1 1 46 1 1 1 2 168.0 18 0 0 52 1 1 0 1 133.0 18 1 1 64 1 0 1 6 37.0 20 1 0 70 1 1 1 3 146.0 20 1 0 45 1 1 1 3 111.0 18 1 0 53 0 1 0 3 19.0 18 1 1 52 1 1 1 6 115.0 15 0 1 45 1 1 0 1 4.0 20 0 1 50 1 1 1 2 52.0 18 0 1 70 1 1 1 3 26.0 20 0 1 50 1 1 1 3 6.0 18 0 0 32 1 0 0 4 55.0 18 0 0 41 1 1 1 5 178.0 15 1 0 39 1 0 1 6 45.5 18 1 1 45 1 1 1 2 90.0 20 0 0 72 1 0 1 2 115.5 20 1 0 46 1 1 1 2 22.0 8 0 0 44 1 0 1 5 89.0 18 0 1 41 1 1 1 4 67.0 20 1 0 59 1 1 0 5 46.0 20 1 1 33 1 1 1 4 94.0 18 0 0 58 0 1 1 2 70.0 20 1 1 31 1 1 1 3 100.0 18 0 0 50 1 1 1 3 22.0 20 1 1 39 1 1 1 4 37.0 15 0 1 54 0 1 1 5 102.0 20 0 0 42 1 0 1 5 131.0 18 0 1 61 1 1 1 3 66.5 13 0 0 33 1 1 1 5 238.0 15 1 1 53 1 1 1 2 58.0 18 0 1 51 1 1 1 5 17.0 20 0 0 54 1 0 1 7 235.0 20 1 1 31 1 1 0 3 98.0 15 0 0 40 1 1 1 3 121.0 18 1 0 55 0 1 1 5 64.0 10 0 1 56 1 1 0 1 61.0 16 1 0 51 1 0 0 2 122.5 8 0 0 62 1 0 1 2 40.0 20 0 0 69 1 0 1 3 86.0 20 0 0 39 1 1 1 5 21.0 18 1 1 47 1 1 1 4 107.0 15 1 0 46 1 1 1 2 139.0 20 1 0 38 1 1 1 3 197.0 15 0 1 74 1
Description Variable Description CreditScore score between 300 and 850 with larger numbers representing increased credit worthiness BureauInquiries number of inquiries about an individual's credit CreditUsage percent of an individual's credit used TotalCredit total amount of credit available to individual CollectionReports number of times an unpaid bill was reported to collection agency MissedPayments number of missed payments HomeOwner 1 if individual is homeowner, 0 if not CreditAge average age of individual's credit TimeOnJob how long the individual has been continuously employed Data CreditScore BureauInquiries CreditUsage TotalCredit CollectionReports MissedPayments HomeOwner CreditAge TimeOnJob 656 7 0.270 18000 0 2 0 6.40 3 Evidence of Overfitting? 696 6 0.300 17000 0 0 1 7.50 5 693 8 0.280 20000 0 0 1 6.30 7 Estimate of Individual 729 7 0.230 16000 0 1 1 6.70 6 695 7 0.230 16000 0 1 1 6.70 6 708 8 0.280 20000 0 0 1 6.30 7 682 6 0.320 8000 0 0 1 7.80 5 719 7 0.270 18000 0 1 0 6.40 3 678 6 0.300 17000 0 0 1 7.50 5 707 8 0.220 21500 0 0 1 6.00 10 646 8 0.270 21500 0 0 0 8.00 13 640 8 0.230 21000 0 0 1 7.10 6 645 7 0.180 19500 0 0 1 9.40 9 779 6 0.160 20000 0 0 1 7.20 14 577 8 0.420 32000 0 2 0 10.10 6 746 6 0.170 19000 0 0 1 8.20 11 651 6 0.480 5000 0 0 1 5.80 5 763 6 0.660 24000 0 0 1 5.40 15 658 7 0.340 22000 0 2 0 7.90 10 589 6 0.310 8000 0 0 1 7.50 5 791 6 0.660 24000 0 0 1 5.40 15 681 6 0.310 20000 0 0 1 5.00 10 821 6 0.260 20000 0 0 1 7.50 8 641 7 0.670 7000 0 2 0 7.90 4 710 6 0.270 20500 0 0 1 7.00 7 726 7 0.250 16000 0 2 1 7.20 8 718 6 0.240 17500 0 0 1 6.00 7 749 7 0.280 18500 0 0 1 7.50 8 668 7 0.270 25000 0 0 1 7.80 11 762 7 0.320 18000 0 0 0 10.90 13 693 8 0.240 19500 0 0 1 7.00 7 748 8 0.140 17000 0 0 1 6.60 7 693 7 0.250 18000 0 0 1 6.40 9 702 6 0.120 17000 0 0 1 7.00 4 600 5 0.270 11000 0 2 1 5.60 7 578 7 0.280 23500 1 1 1 6.40 15 649 6 0.390 11500 0 0 1 5.00 7 730 7 0.330 16000 0 0 1 4.60 10 617 7 0.240 20500 0 0 1 5.80 2 641 7 0.240 20500 0 0 1 5.80 2 729 6 0.230 19500 0 1 0 5.20 5 710 6 0.240 19500 0 1 0 5.20 5 703 7 0.310 13000 0 1 1 6.40 6 729 6 0.240 13500 0 1 1 8.50 5 678 6 0.230 13000 1 1 1 8.50 5 775 7 0.180 15500 0 1 1 7.00 7 485 6 0.450 15000 1 4 1 7.40 6 624 6 0.460 12500 1 2 1 7.40 6 693 7 0.310 13000 0 1 1 6.40 6 635 6 0.190 18500 1 1 1 7.40 6 742 7 0.190 15500 0 1 1 6.10 12 753 6 0.250 14500 0 0 1 8.00 10 777 6 0.160 16500 0 0 1 6.70 9 733 6 0.180 17500 0 0 1 5.70 9 652 6 0.200 30500 0 0 0 5.30 4 748 6 0.250 17500 0 1 1 7.00 10 681 7 0.210 17000 0 2 0 7.80 5 697 6 0.190 13000 0 0 1 5.70 3 715 6 0.380 7500 0 0 0 5.60 7 685 7 0.200 18000 0 0 1 5.70 6 696 6 0.220 12000 0 0 0 6.80 2 691 6 0.190 13000 0 0 1 5.70 3 577 7 0.470 4500 0 1 0 5.50 8 652 6 0.380 7500 0 0 0 5.60 7 673 7 0.240 13500 0 0 1 6.90 7 628 6 0.350 5000 0 0 1 8.30 4 714 6 0.260 13000 0 0 1 7.80 14 619 6 0.250 7500 0 2 1 6.40 6 819 6 0.230 14500 0 0 1 9.10 9 626 7 0.240 15500 0 0 1 5.50 5 679 6 0.270 21500 1 2 0 7.00 4 613 6 0.300 12500 1 2 1 9.50 5 583 6 0.270 15000 1 2 1 10.00 7 657 8 0.230 24000 0 0 0 7.30 4 816 6 0.230 14500 0 0 1 9.10 9 563 7 0.240 15500 1 1 1 5.50 5 736 7 0.180 18000 0 0 1 5.10 15 714 7 0.320 17000 0 0 1 9.00 13 629 7 0.180 16000 0 0 0 8.90 4 567 6 0.540 15000 0 0 1 5.00 4 703 6 0.220 15500 0 0 1 11.80 8 661 7 0.200 18000 0 1 1 9.60 4 575 7 0.340 11000 1 2 1 6.00 7 705 7 0.220 15000 0 1 1 6.50 5 597 7 0.430 31500 0 1 0 6.10 3 733 7 0.440 30000 0 1 0 6.10 3 743 7 0.390 30500 0 1 0 6.10 3 663 6 0.250 15500 1 1 1 7.10 6 630 7 0.430 30500 0 1 0 6.10 3 742 7 0.440 30000 0 1 0 6.10 3 682 7 0.390 31500 0 1 0 6.10 3 579 6 0.270 22500 0 3 0 7.00 4 761 6 0.240 16500 0 0 1 6.80 14 741 6 0.210 16500 0 0 1 6.80 14 731 7 0.170 16000 0 0 1 6.50 11 746 7 0.260 13500 0 2 0 6.60 4 650 6 0.340 33000 0 2 1 7.40 3 705 8 0.265 18000 0 0 0 5.20 11 527 9 0.360 24000 0 0 0 4.30 7 687 6 0.340 33000 0 2 1 7.40 3 622 7 0.250 19500 0 2 0 6.30 4 588 7 0.120 17000 1 2 1 6.20 5 561 6 0.210 14000 1 3 1 5.20 5 593 7 0.305 21000 1 2 0 6.00 4 573 7 0.250 19500 1 2 0 6.30 4 651 7 0.130 17000 0 0 1 5.60 4 570 7 0.120 18000 1 3 1 6.20 5 676 7 0.230 17500 0 2 1 8.30 4 664 7 0.230 17500 0 2 1 8.30 4 608 6 0.330 15000 1 2 1 9.90 7 706 6 0.170 27000 0 1 0 5.40 3 546 7 0.270 24000 1 4 0 7.70 3 648 7 0.310 25000 0 2 0 7.60 4 571 6 0.410 18000 0 1 1 7.30 4 557 6 0.410 18000 0 1 1 7.30 4 510 5 0.485 7000 1 1 1 6.10 6 746 6 0.310 12000 0 0 1 6.90 10 666 7 0.140 21000 0 0 1 6.40 12 558 7 0.310 26000 1 2 0 7.60 4 553 7 0.320 25000 1 2 0 7.60 4 603 5 0.360 6000 0 0 1 7.60 7 621 7 0.240 17000 0 0 0 8.40 3 634 7 0.160 16500 0 0 1 5.10 6 666 6 0.190 15000 0 0 1 5.30 4 735 6 0.130 23500 0 1 1 5.40 6 685 6 0.190 19000 0 0 1 7.00 10 545 7 0.390 12500 0 0 1 6.50 8 693 6 0.240 16000 0 2 1 8.10 6 754 6 0.300 28000 0 1 1 8.70 9 746 6 0.300 28000 0 1 1 8.70 9 627 5 0.260 13500 0 0 1 5.80 8 687 6 0.240 16000 0 2 1 8.10 6 646 6 0.425 20000 0 3 1 8.00 4 578 6 0.240 14500 0 2 1 7.60 4 606 6 0.270 12000 0 2 1 7.70 3 546 6 0.270 16500 0 3 1 8.80 5 687 8 0.230 20000 0 0 0 5.10 9 556 7 0.370 34500 0 1 1 6.10 3 756 6 0.190 18000 0 0 1 8.40 9 689 8 0.280 19500 0 0 1 7.40 12 633 6 0.310 17000 0 0 1 6.60 7 574 7 0.370 34500 0 1 1 6.10 3 665 7 0.210 20000 0 0 1 8.40 9 720 8 0.210 20500 0 0 1 7.10 6 743 8 0.200 20000 0 0 0 8.60 10 703 6 0.255 18500 0 0 0 5.70 9 670 5 0.160 14500 0 2 1 5.30 7 453 6 0.595 9000 1 2 1 5.00 4 756 6 0.340 16500 0 0 1 8.00 13 706 6 0.250 15000 0 0 0 5.20 5 681 7 0.220 20000 0 1 0 4.50 11 661 7 0.180 24000 0 0 1 6.70 6 693 6 0.250 15000 0 0 0 5.20 5 624 7 0.180 21500 0 0 1 6.20 8 712 8 0.230 20000 0 0 0 12.10 6 707 7 0.240 21000 0 1 0 6.70 3 722 7 0.240 21000 0 1 0 6.70 3 752 6 0.320 12000 0 0 1 6.20 14 825 5 0.440 4000 0 0 1 4.30 13 762 5 0.440 5000 0 0 1 4.30 13 772 6 0.320 12000 0 0 1 6.20 14 569 6 0.220 29000 1 1 0 6.30 4 579 6 0.360 16000 0 0 1 5.80 8 735 7 0.240 21000 0 1 0 6.70 3 648 6 0.240 18500 1 2 1 7.50 5 558 7 0.230 20000 1 3 1 7.40 6 653 8 0.270 23000 0 2 1 8.80 5 724 6 0.460 9000 0 0 0 6.80 14 608 7 0.290 16500 0 1 0 8.90 4 559 9 0.420 25000 0 0 0 4.00 7 700 7 0.300 24000 0 0 0 8.10 15 743 7 0.190 22500 0 0 1 5.00 10 503 7 0.480 20500 0 1 0 5.20 11 772 6 0.220 21500 0 0 1 4.50 11 565 7 0.270 16500 1 2 0 9.60 7 734 6 0.230 20000 0 1 0 4.20 11 457 7 0.320 26500 0 3 0 6.80 14 628 5 0.230 16000 1 2 1 5.20 5 496 6 0.670 5500 1 2 0 5.10 3 745 6 0.250 16000 0 1 1 10.60 4 690 6 0.330 15500 0 2 1 9.90 4 626 7 0.340 7500 0 2 0 6.60 4 634 6 0.280 21000 0 2 0 7.10 3 688 6 0.270 20000 1 1 1 8.80 5 616 6 0.260 29000 0 2 0 9.90 4 593 6 0.290 29000 0 2 0 9.90 4 662 6 0.240 21500 0 2 0 9.70 6 603 5 0.300 12500 0 0 1 7.00 10 802 6 0.530 17500 0 0 1 8.10 15 521 6 0.280 16000 0 3 0 8.70 3 706 6 0.280 14000 0 1 0 8.70 3 560 6 0.280 21000 0 2 0 7.10 3 718 6 0.280 18000 0 0 0 5.20 11 590 6 0.150 18000 0 0 1 6.80 5 566 6 0.290 23000 2 2 0 6.30 4 736 6 0.300 22500 0 1 0 5.30 4 596 6 0.290 23000 2 2 0 5.30 4 593 6 0.260 13000 1 2 1 7.70 3 626 7 0.320 12000 0 2 0 7.40 3 562 6 0.260 13000 1 2 1 7.70 3 627 6 0.270 14000 0 2 1 7.90 4 566 7 0.320 13000 1 2 0 7.40 3 631 6 0.540 16000 1 2 1 7.80 5 707 6 0.260 17000 0 0 1 7.00 13 501 5 0.280 19500 1 1 1 7.60 7 649 6 0.210 26000 0 1 1 6.40 3 606 7 0.160 17000 0 0 1 5.60 4 414 10 0.440 47000 0 3 0 7.70 6 573 6 0.570 15500 0 0 1 11.60 7 711 6 0.400 15500 0 1 1 11.50 5 606 5 0.245 13500 0 0 1 5.50 8 773 6 0.180 19000 0 0 1 8.60 10 645 7 0.160 17000 0 0 1 5.60 4 733 6 0.130 14500 0 0 1 5.10 6 757 6 0.250 12500 0 0 1 6.30 10 612 5 0.260 13000 0 1 1 5.20 5 627 7 0.270 19000 0 2 0 4.00 10 581 5 0.260 13000 0 1 1 5.20 5 550 5 0.280 13000 0 2 1 6.20 5 627 7 0.230 19000 0 2 0 4.00 10 592 7 0.270 19000 0 2 0 4.00 10 657 7 0.685 10500 0 1 0 8.30 4 686 6 0.250 13500 0 0 1 6.30 10 743 6 0.190 15000 0 0 1 5.30 4 658 6 0.495 11000 0 0 1 8.20 8 621 7 0.240 21500 0 0 1 5.10 3 699 6 0.170 16000 0 2 1 7.10 6 730 7 0.250 16000 0 2 1 7.30 4 729 6 0.170 16000 0 1 1 7.10 6 578 7 0.240 21500 0 0 1 5.10 3 485 6 0.640 6000 1 2 1 6.70 3 708 8 0.280 20000 0 1 1 7.80 5 730 8 0.270 19500 0 1 1 7.50 5 697 7 0.230 19000 0 1 0 6.00 4 709 7 0.230 19000 0 1 0 6.00 4 733 7 0.230 19000 0 1 0 6.00 4 717 7 0.230 19000 0 1 0 6.00 4 711 6 0.520 16000 0 1 1 7.80 5 745 7 0.260 29500 0 0 1 6.30 10 696 6 0.250 10500 0 1 1 9.80 5 620 7 0.320 11500 0 2 1 6.10 3 568 7 0.310 14000 0 0 1 7.20 8 747 7 0.210 18500 0 0 1 5.20 11 672 6 0.240 17000 0 2 1 8.10 6 555 6 0.400 29000 0 0 1 6.10 3 683 6 0.180 19000 0 3 1 11.90 10 735 6 0.210 13500 0 0 1 9.80 14 768 5 0.200 13500 0 0 1 5.70 9 694 5 0.190 14000 0 0 1 5.70 9 612 6 0.410 8000 0 0 1 6.00 7 457 5 0.210 17000 1 5 1 10.00 7 408 8 0.260 13500 1 5 0 7.40 6 577 6 0.400 29000 0 0 1 6.10 3 322 5 0.240 26000 1 6 1 6.10 12 709 5 0.240 19500 0 1 1 7.90 4 798 6 0.260 18500 0 0 1 8.80 5 726 6 0.350 15000 0 0 1 6.00 10 772 6 0.350 15000 0 0 1 6.00 10 746 6 0.230 19500 0 0 1 7.40 12 515 5 0.360 21000 0 1 1 5.20 11 728 6 0.115 17500 0 0 1 6.60 7 580 6 0.290 21000 0 1 0 7.70 3 575 6 0.280 21000 0 0 1 4.60 7 652 7 0.290 20000 0 2 0 8.80 5 657 6 0.240 18500 0 2 0 7.80 8 632 6 0.290 21000 0 1 0 7.70 3 730 6 0.320 12000 0 1 1 7.60 4 615 5 0.580 4500 0 0 1 8.10 6 714 5 0.585 3500 0 0 1 8.10 6 715 5 0.590 3500 0 0 1 8.10 6 670 6 0.320 13000 1 1 1 7.60 4 556 5 0.600 4500 0 0 1 8.10 6 587 5 0.250 14000 0 0 1 5.90 4 584 6 0.580 16000 0 0 1 5.00 4 623 7 0.290 28000 0 2 0 9.50 5 683 6 0.190 21500 0 2 1 8.40 6 715 6 0.200 20500 0 1 1 8.40 6 539 7 0.260 22000 0 1 0 7.80 8 437 6 0.320 19000 1 2 0 7.80 8 687 7 0.300 25500 0 0 1 10.20 14 767 7 0.240 18000 0 0 1 5.80 14 790 6 0.310 29000 0 0 1 9.90 13 463 6 0.440 20500 0 4 0 9.50 8 589 6 0.340 16000 1 2 1 7.90 4 625 7 0.350 12000 0 2 0 7.40 3 643 7 0.320 12500 0 2 0 7.40 3 695 6 0.280 16500 1 1 1 7.10 6 705 7 0.230 19500 0 1 0 7.00 4 728 7 0.230 19500 0 1 0 7.00 4 766 7 0.230 18500 0 1 0 7.00 4 724 7 0.230 19500 0 1 0 7.00 4 719 5 0.150 15500 0 1 1 6.50 8 646 7 0.280 21000 0 2 0 6.30 4 696 6 0.280 11000 0 1 1 9.40 6 375 9 0.590 22000 1 8 1 5.50 2 662 6 0.330 13500 0 2 1 8.20 5 619 8 0.390 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11.90 7 703 7 0.320 18500 0 0 1 9.60 13 721 7 0.170 14500 0 0 1 9.20 8 567 7 0.260 17000 0 1 1 7.20 11 686 8 0.280 17000 0 2 1 6.70 6 638 7 0.300 19500 0 0 1 9.00 7 707 8 0.250 19000 0 0 1 5.50 11 654 7 0.280 14500 0 2 1 9.50 8 687 6 0.240 19000 0 0 1 5.50 14 655 7 0.220 17000 0 0 0 6.50 8 726 8 0.280 17000 0 1 1 6.70 6 748 8 0.450 14000 0 1 0 7.20 11 701 6 0.230 16500 0 1 1 6.40 6 727 8 0.450 14000 0 1 0 7.20 11 467 7 0.230 15000 1 4 0 6.60 4 572 7 0.280 30000 0 2 0 6.70 3 590 7 0.270 31500 0 2 0 6.70 3 750 7 0.200 18000 0 0 0 8.50 5 682 6 0.250 18500 0 1 1 5.50 11 713 7 0.200 18000 0 0 0 8.50 5 744 6 0.250 17500 0 1 1 5.50 11 695 8 0.200 15500 0 0 0 6.50 5 648 6 0.390 17500 0 2 1 7.10 6 634 7 0.230 20000 0 0 1 11.10 6 708 6 0.440 21000 0 0 1 6.50 5 588 7 0.280 10500 0 2 1 7.20 5 498 6 0.340 12000 1 4 1 6.00 4 730 6 0.150 14500 0 1 1 6.80 8 721 6 0.440 20000 0 0 1 6.50 5 574 7 0.290 10000 0 2 1 7.30 4 608 7 0.280 10500 0 2 1 7.20 5 610 6 0.230 23500 1 2 0 8.40 3 580 6 0.230 22000 0 2 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6.60 4 501 6 0.330 11000 0 1 1 6.50 11 341 7 0.480 21500 2 4 0 8.20 8 695 7 0.200 16000 0 2 1 6.00 13 654 7 0.320 15500 0 1 1 6.60 13 686 7 0.200 16000 0 2 1 6.00 13 711 7 0.220 14500 0 0 1 6.40 6 601 9 0.230 29000 0 3 0 7.90 4 463 6 0.270 11500 1 4 1 9.80 5 451 6 0.270 11500 1 4 1 9.50 5 688 7 0.230 21000 0 0 1 8.60 7 742 6 0.150 14000 0 0 1 6.20 8 699 6 0.260 14500 0 0 1 7.00 10 762 6 0.150 14000 0 0 1 6.20 8 604 7 0.200 35000 0 2 0 6.10 3 487 6 0.300 16500 1 4 1 8.70 6 526 6 0.300 17000 1 3 1 8.70 6 477 7 0.210 20500 0 3 0 6.90 10 777 6 0.460 13000 0 0 1 7.00 13 789 7 0.280 12000 0 0 1 7.10 9 746 6 0.240 14500 0 1 1 10.30 7 696 6 0.170 17000 0 0 1 7.80 5 681 6 0.170 18000 0 0 1 7.80 5 546 6 0.695 28500 1 3 1 7.10 3 571 7 0.270 15500 1 2 1 8.90 7 633 8 0.300 13500 0 2 0 9.30 4 714 6 0.190 13500 0 0 1 6.40 12 690 8 0.360 19500 0 0 1 7.70 12 659 6 0.160 13000 0 0 1 8.90 7 458 9 0.190 24000 0 3 0 9.00 7 499 9 0.160 26500 0 2 0 7.60 7 667 8 0.260 14000 0 2 0 8.00 7 698 8 0.330 19000 0 0 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6.10 9 679 7 0.240 12000 0 2 1 6.60 7 581 5 0.600 7000 0 3 1 6.70 9 714 5 0.445 13000 0 0 1 5.50 8 718 6 0.280 14000 0 0 1 5.10 12 628 6 0.440 10000 1 2 1 6.80 2 585 7 0.240 14500 0 2 1 6.00 4 615 8 0.310 37500 0 2 0 13.10 3 680 8 0.320 14000 0 0 0 7.40 15 582 7 0.240 14500 0 2 1 6.00 4 585 8 0.310 37500 0 2 0 13.10 3 685 7 0.130 20000 0 0 1 7.40 12 690 9 0.140 19500 0 0 0 8.80 11 738 7 0.200 18500 0 0 1 9.40 12 547 6 0.150 19500 0 2 1 5.80 8 627 7 0.230 21000 0 0 1 12.10 6 560 8 0.330 12000 0 1 1 7.90 7 705 7 0.170 12000 0 1 1 6.60 7 681 6 0.120 16000 0 0 1 6.30 7 696 5 0.180 19000 0 0 1 10.70 9 615 5 0.150 15000 0 0 1 7.90 4 666 6 0.230 14500 0 0 1 8.60 7 723 7 0.170 12000 0 1 1 6.60 7 543 7 0.340 20500 1 2 0 7.50 5 634 6 0.680 13000 0 0 1 6.90 4 744 7 0.220 15500 0 0 0 5.70 15 583 6 0.280 14500 0 0 1 6.10 3 616 6 0.400 12000 1 3 1 8.20 5 635 6 0.190 12500 0 2 1 10.30 7 495 7 0.230 14000 0 4 1 11.00 7 741 6 0.140 21000 0 0 1 10.30 10 773 6 0.150 22000 0 1 1 10.90 7 672 7 0.150 18000 0 0 1 6.60 13 707 6 0.330 17000 0 1 0 7.90 4 658 7 0.300 14000 0 2 1 8.90 10 706 7 0.230 16500 0 0 0 9.40 9 748 8 0.130 12500 0 0 0 5.60 10 763 6 0.210 17000 0 0 1 6.50 14 613 8 0.400 21500 0 0 1 7.90 4 737 5 0.340 15500 0 0 1 6.70 15 738 6 0.120 12500 0 0 1 6.60 10 728 9 0.655 10500 0 0 0 15.80 14 585 6 0.260 21000 0 2 1 7.90 4 741 5 0.340 15500 0 0 1 6.70 15 707 5 0.300 16000 0 0 1 6.70 15 701 7 0.150 15000 0 0 1 5.50 5 671 7 0.370 16500 0 0 1 5.70 12 687 7 0.350 12500 0 0 0 9.90 7 765 7 0.320 11000 0 0 0 9.90 7 682 7 0.100 17500 0 0 0 10.60 10 656 6 0.250 16500 0 1 1 4.00 13 596 7 0.310 9500 0 0 1 6.80 5 721 7 0.180 14000 0 0 1 6.60 4 683 8 0.170 15500 0 0 0 4.70 15 671 7 0.190 14500 0 0 0 8.90 4 658 7 0.320 13500 0 0 0 6.30 13 599 7 0.310 9500 0 0 1 6.80 5 703 6 0.210 14500 0 0 1 7.60 10 751 7 0.160 18000 0 0 0 5.60 10 709 8 0.170 15500 0 0 0 4.70 15 616 6 0.240 20000 0 2 1 6.60 4 708 7 0.190 13500 0 0 0 8.90 4 670 7 0.180 15000 0 0 1 6.60 4 731 6 0.300 12500 0 0 1 7.90 4 688 6 0.280 13500 0 0 1 5.10 9 747 6 0.310 15000 0 1 0 8.40 6 677 6 0.230 12500 0 0 1 8.90 7 667 6 0.280 13500 0 0 1 5.10 9 659 5 0.230 15000 0 0 1 5.90 10 722 6 0.220 25000 0 1 0 7.40 3 627 7 0.180 19500 0 0 1 7.40 9 710 6 0.310 16000 0 1 0 8.40 6 671 6 0.300 12500 0 0 1 7.90 4 776 6 0.460 15500 0 0 1 9.50 11 630 6 0.230 19000 0 0 1 6.40 3 569 6 0.230 19000 0 0 1 6.40 3 584 6 0.230 19000 0 0 1 6.40 3 670 6 0.260 19000 1 1 1 5.20 5 667 6 0.260 19500 1 1 1 5.20 5 706 7 0.280 19500 0 1 1 9.80 5 594 6 0.230 19000 0 0 1 6.40 3 698 6 0.230 21000 0 2 1 7.90 4 627 7 0.250 18000 0 2 1 11.70 3 630 7 0.250 18000 0 2 1 11.70 3 637 5 0.200 12000 0 1 1 6.00 7 637 6 0.210 23000 0 2 1 6.30 4 723 6 0.230 21000 0 1 1 7.90 4 742 6 0.240 18500 0 1 1 7.20 5 712 7 0.250 14000 0 1 1 9.30 7 610 7 0.250 18000 0 2 1 11.70 3 668 6 0.160 15500 0 0 1 6.40 9 676 5 0.280 14500 0 0 1 8.00 7 688 7 0.180 16500 0 2 0 5.70 9 705 7 0.260 15000 0 0 1 5.00 13 608 8 0.370 33000 0 2 0 12.90 4 726 7 0.400 13500 0 0 1 9.90 13 677 7 0.260 12500 0 0 1 8.20 8 744 7 0.180 15500 0 1 0 5.70 9 598 6 0.230 17000 0 1 1 6.50 8 663 5 0.200 16500 0 0 1 7.40 6 685 6 0.170 15500 0 0 0 6.50 8 695 6 0.350 14000 1 1 1 7.70 6 701 6 0.290 15500 0 0 1 10.20 11 637 6 0.300 12000 1 2 1 7.60 4 627 7 0.510 18000 0 2 0 7.10 6 607 7 0.510 18000 0 0 0 7.00 7 706 6 0.290 15500 0 0 1 10.20 11 724 7 0.290 14000 0 0 1 7.90 7 716 6 0.350 14000 0 1 1 7.70 6 741 6 0.170 15500 0 0 0 6.50 8 696 7 0.200 14000 0 0 1 7.40 6 568 6 0.615 22000 0 0 1 5.90 4 732 6 0.320 14000 0 0 0 7.20 14 658 6 0.200 10500 0 0 1 6.90 4 534 6 0.615 22000 0 0 1 5.90 4 691 8 0.230 14000 0 2 1 10.50 5 704 6 0.270 16500 0 0 0 6.50 8 719 6 0.270 16500 0 0 0 6.50 8 742 6 0.440 11000 0 0 1 7.40 15 673 7 0.340 15000 0 0 0 6.40 9 725 7 0.260 16500 0 0 0 8.00 7 840 5 0.170 16000 0 1 1 13.40 12 724 7 0.260 16500 0 0 0 8.00 7 797 5 0.170 17000 0 1 1 13.40 12 658 6 0.170 19000 0 0 1 9.00 13 704 7 0.430 16000 0 0 1 6.80 14 811 5 0.315 12500 0 0 1 6.70 12 575 5 0.170 16000 0 1 1 4.80 8 648 6 0.340 9000 1 3 1 7.60 4 720 8 0.330 16000 0 2 1 7.00 7 540 5 0.120 15000 0 1 1 6.60 4 687 5 0.130 13000 0 0 1 7.90 4 716 7 0.180 17500 0 0 1 8.60 7 726 7 0.160 18000 0 0 1 8.60 7 585 6 0.260 8500 1 1 1 7.10 3 602 7 0.320 18500 0 2 1 6.10 9 732 7 0.300 17000 0 0 1 5.30 13 705 7 0.160 15000 0 1 0 5.50 5 677 6 0.270 15500 0 0 1 5.60 10 663 6 0.160 19500 0 0 0 8.00 13 690 7 0.160 15000 0 1 0 5.50 5 742 7 0.300 17000 0 0 1 5.30 13 560 7 0.320 18500 1 2 1 6.10 9 700 6 0.440 22000 0 2 1 8.40 3 715 6 0.200 12000 0 0 1 9.40 9 751 6 0.290 16000 0 0 1 5.30 16 769 7 0.390 16000 0 0 0 9.50 14 811 7 0.360 15000 0 0 0 4.10 12 834 7 0.360 15000 0 0 0 4.10 12 759 7 0.360 16000 0 0 0 4.80 11 667 7 0.200 19000 0 0 1 8.90 10 708 7 0.390 17000 0 0 0 9.50 14 634 6 0.200 19500 0 0 0 6.20 11 540 6 0.235 19000 0 1 1 6.60 13 676 7 0.965 31000 0 1 1 10.10 12 749 7 0.200 15500 0 1 1 8.20 8 741 7 0.200 15500 0 1 1 8.20 8 657 7 0.200 16500 0 1 1 8.20 8 624 6 0.240 13500 1 1 1 7.30 4 744 8 0.300 18000 0 0 0 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16500 1 1 0 7.00 4 580 7 0.230 18000 0 0 0 8.00 7 605 7 0.200 20500 0 1 0 6.70 12 720 5 0.160 19500 0 0 1 8.80 8 729 6 0.210 14000 0 0 1 6.00 10 734 6 0.330 13000 0 0 1 6.60 10 749 5 0.180 29000 0 0 1 9.00 13 838 6 0.290 14500 0 0 1 9.80 14 716 6 0.330 13000 0 0 1 6.60 10 727 6 0.210 18000 0 0 1 10.50 8 660 7 0.210 17500 0 0 0 7.60 7 706 6 0.210 14000 0 0 1 6.00 10 663 5 0.110 17000 0 0 1 7.60 13 676 6 0.150 17000 0 0 1 6.90 13 705 5 0.160 19500 0 0 1 8.80 8 705 5 0.190 23000 0 0 1 7.20 8 764 5 0.180 29000 0 0 1 9.00 13 693 6 0.480 17000 0 0 1 7.10 15 649 6 0.230 12500 0 0 0 4.80 8 657 6 0.170 15500 0 0 1 5.90 13 738 6 0.480 16000 0 0 1 7.10 15 675 6 0.150 20000 0 0 0 7.20 11 700 4 0.170 18000 0 2 1 13.00 13 838 5 0.210 15000 0 0 1 14.20 14 682 5 0.230 19000 0 0 1 14.30 13 678 6 0.150 20000 0 0 0 7.20 11 600 6 0.220 16500 0 0 1 5.10 9 575 6 0.150 29500 0 3 0 6.90 4 717 5 0.320 17500 0 0 1 6.10 15 655 5 0.370 16000 0 0 1 5.10 12 559 7 0.250 19500 0 1 0 7.10 9 719 7 0.210 14000 0 0 0 6.40 12 631 7 0.240 16000 0 0 1 5.70 6 739 6 0.475 16500 0 0 1 7.20 17 780 7 0.280 16000 0 0 0 9.40 15 711 6 0.400 16000 0 0 1 6.40 15 582 6 0.410 16500 0 0 1 6.50 8 581 6 0.200 16000 0 1 1 8.50 11 455 8 0.220 20000 0 3 0 5.50 8 744 8 0.360 18000 0 0 0 5.00 16 836 5 0.285 13500 0 0 1 5.20 14 655 6 0.200 16000 0 0 1 5.60 7 567 6 0.420 24000 1 2 1 7.00 4 740 6 0.160 17000 0 1 1 12.00 13 757 6 0.125 18000 0 0 1 7.10 12 610 6 0.440 14000 1 2 1 8.00 7 571 7 0.310 20500 1 2 1 8.90 7 624 6 0.420 23000 1 2 1 7.00 4 619 8 0.180 15000 0 0 0 5.30 10 627 6 0.210 14000 1 1 1 6.00 4 698 6 0.160 18500 0 0 1 8.50 8 725 6 0.220 16000 0 0 1 8.70 12 580 6 0.360 8000 0 1 1 7.20 5 738 5 0.210 12500 0 0 1 7.20 11 741 6 0.250 16000 0 0 1 8.40 9 560 7 0.310 14000 1 1 0 6.40 6 573 6 0.260 24000 0 2 1 6.90 4 746 5 0.210 12500 0 0 1 7.20 11 651 6 0.200 16500 0 0 1 7.90 10 664 6 0.180 16000 0 0 1 7.90 10 599 6 0.370 11000 0 2 1 7.50 5 564 6 0.360 8000 0 1 1 7.20 5 722 6 0.220 16000 0 0 1 8.70 12 630 7 0.180 16000 0 2 0 5.90 4 678 6 0.140 20000 0 0 0 8.20 11 710 6 0.140 19000 0 0 0 8.20 11 658 6 0.440 14000 0 0 1 5.10 15 751 7 0.360 20000 0 0 1 6.50 17 711 5 0.280 14000 0 0 0 7.60 10 605 6 0.160 17000 0 0 1 6.10 9 506 7 0.280 22000 0 1 0 6.40 9 723 6 0.390 14500 0 1 1 8.50 8 825 6 0.440 22500 0 0 1 4.00 16 740 6 0.220 15500 0 0 0 7.40 9 691 6 0.220 14500 0 0 0 7.30 4 562 7 0.250 17000 0 3 0 7.30 7 811 5 0.155 15500 0 0 1 12.70 12 693 7 0.310 15500 0 0 0 4.00 13 771 7 0.310 15500 0 0 0 4.00 13 662 6 0.220 15500 0 0 0 7.30 4 782 5 0.210 20000 0 0 1 14.80 11 759 5 0.155 16500 0 0 1 12.70 12 715 6 0.250 16000 0 1 1 7.60 7 663 6 0.220 15500 0 0 0 7.40 9 597 5 0.210 15500 0 0 1 6.40 6 508 7 0.270 16000 0 1 0 4.20 11 629 5 0.170 14500 0 0 1 6.40 6 644 7 0.250 16000 0 2 0 7.30 7 795 7 0.120 13500 0 0 1 5.40 6 839 7 0.120 13500 0 0 1 5.40 6 712 7 0.290 17000 0 0 1 6.10 9 591 7 0.300 16000 0 0 0 9.80 8 633 6 0.260 24000 0 2 1 7.90 4 764 7 0.120 14500 0 0 1 5.40 6 748 7 0.290 16000 0 0 1 6.10 9 796 4 0.330 15500 0 1 1 8.00 19 662 5 0.290 15000 0 0 1 5.00 10 668 5 0.290 15000 0 0 1 5.00 10 726 6 0.260 24000 0 1 1 6.20 5 728 6 0.280 26000 0 0 0 5.00 4 629 6 0.280 13500 0 0 0 8.00 4 639 7 0.200 12000 0 0 1 7.00 7 606 6 0.270 13500 0 0 0 8.00 4 607 6 0.280 13500 0 0 0 8.00 4 719 6 0.290 15000 0 0 1 9.20 14 562 7 0.350 14000 0 1 1 6.90 10 707 8 0.120 19000 0 0 0 8.00 13 745 6 0.120 15000 0 0 0 8.10 12 622 7 0.200 12000 0 0 1 7.00 7 727 7 0.400 13000 0 0 0 8.60 16 739 7 0.110 17000 0 0 0 8.00 10 653 6 0.230 21500 0 0 1 8.00 10 565 6 0.380 20000 0 0 0 7.60 4 702 7 0.380 15500 0 0 0 7.00 16 576 5 0.190 14000 0 1 1 9.80 8 762 5 0.340 13000 0 0 1 7.00 16 685 6 0.230 15000 0 0 0 8.00 4 683 6 0.230 15000 0 0 0 8.00 4 578 8 0.310 17500 0 1 0 4.50 11 711 6 0.200 15000 0 0 0 6.00 10 560 8 0.310 17500 0 1 0 4.50 11 599 7 0.260 13000 0 0 0 6.70 6 654 6 0.220 12000 0 0 0 6.20 8 746 6 0.230 15000 0 0 0 8.00 4 670 7 0.190 21000 0 0 0 7.70 6 662 8 0.140 17500 0 2 0 7.00 10 724 6 0.320 19500 0 0 1 5.30 13 673 6 0.230 10000 0 0 0 7.10 6 749 6 0.230 10000 0 0 0 7.10 6 756 6 0.360 13000 0 0 0 4.60 13 758 6 0.380 21000 0 0 1 4.20 14 769 8 0.230 13000 0 0 0 5.50 8 713 7 0.200 15500 0 1 1 8.20 8 698 6 0.260 16000 0 2 1 5.00 13 728 6 0.300 15000 0 0 0 4.10 15 736 6 0.180 14000 0 0 0 6.70 9 691 6 0.180 15000 0 0 0 6.70 9 704 6 0.180 14000 0 0 0 6.70 9 694 7 0.190 16500 0 0 1 7.20 11 707 6 0.160 16000 0 1 1 6.00 10 736 5 0.270 16000 0 1 1 4.80 14 732 6 0.370 14000 0 1 1 6.80 11 710 6 0.200 13500 0 0 0 6.50 8 724 6 0.180 14000 0 0 0 6.70 9 735 6 0.180 14000 0 0 0 6.70 9 696 6 0.280 18000 0 0 0 5.50 14 763 6 0.350 18000 0 0 0 7.30 13 669 6 0.250 17500 0 1 0 8.90 10 723 6 0.320 15000 0 0 0 9.90 16 699 6 0.180 14000 0 0 0 6.70 9 765 6 0.180 14000 0 0 0 6.70 9 752 6 0.200 13500 0 0 0 6.50 8 717 6 0.370 14000 0 1 1 6.80 11 713 7 0.190 15500 0 0 1 7.20 11 729 6 0.180 18000 0 0 1 7.00 10 687 6 0.300 19000 0 1 0 5.30 13 681 6 0.160 17000 0 2 1 6.00 10 744 5 0.270 16000 0 1 1 4.80 14 705 5 0.300 17500 0 1 1 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MNGT 379 - Business Analytics Module 7 Predictive Data Mining Homework Due to the realistic size of these data sets, XLMiner may take several minutes to complete execution for some of these problems. Problem 1 – Salmons Stores Salmons Stores operates a national chain of women’s apparel stores. Five thousand copies of an expensive four-color sales catalog have been printed, and each catalog includes a coupon that provides a $50 discount on purchases of $200 or more. Salmons would like to send the catalogs only to customers who have the highest probability of using the coupon. The file “Module 7 SalmonsStores.xlsx “contains data from an earlier promotional campaign. For each of 1,000 Salmons customers, three variables are tracked: last year’s total spending at Salmons, whether they have a Salmons store credit card, and whether they used the promotional coupon they were sent. Use the data in “Module 7 SalmonsStores.xlsx” to complete the steps below. Follow the instructions below to partition the data into Training, Validation, and Test Sets, and perform a Logistic Regression on the data. Step 1: Open the Classify toolpack (Data Mining Tab > Data Mining Group) and select Logistic Regression . On Page 1, move Spending and Card to the Selected Variables and put Coupon as the Output Variable. Step 2: On Page 2, select Partition Data . In the Partitioning dialogue box, activate the User defined partition percentages and set Training to 40%, Validation to 40%, and Test to 20%. Then choose Done . Step 3: Still on Page 2, select Feature Selection , then check the box next to Perform Feature Selection. Set the Method to Best Subsets and Number of Subsets to 4. Step 4: On Page 3, you will see a series of blue-bordered boxes labeled Score Training Data, Score Validation Data, and Score Test Data. Check the boxes next to Detailed Report and Lift Charts in ONLY the Score Training Data (but leave all three Summary Report boxes checked). Make sure your option boxes match the screenshot below, then click Finish. As is indicated in the italicized note at the top of this document, these data sets can take quite a while to analyze, and even the progress bar may be misleading as it will usually reset several times during the “executing” process. Once the process completes, a number of new worksheets will appear alongside of SalmonsStores, but they may show up as blank at first. For some reason, you may have to wait another minute or so for the information to show up on the tabs – don’t be alarmed by this! Step 5: Navigate to the worksheet “LogReg_Output” and scroll down to the Coefficients section beginning in row 78. Interpret this output by completing the sentence in the text box labeled “Interpretation of Regression Equation” on the SalmonsStores worksheet. Step 6: Now navigate to the worksheet “LogReg_TrainingLiftChart”. Look at the Decile Chart Data beginning in cell I16. Column L of the table, labeled “Decile/Global Mean”, contains the lift multiplier for each decile of the data. Meaning, a value of 1 indicates that the decile is equally likely to correctly predict observations (customers in this case) compared to choosing randomly, while a value of 1.35 indicates that the decile is 35% more likely to predict customers correctly. With this in mind, consider the first decile, and interpret the lift in the text box labeled “Interpretation of Lift” on the SalmonsStores worksheet. Round your answer to the nearest whole percent. Step 7: Finally, navigate to the worksheet “LogReg_TrainingScore” and consider cell D26, which contains the Accuracy percentage for the Training Data. Also navigate to the “LogReg_ValidationScore” and “LogReg_TestScore” worksheets and compare the three Accuracy values (also in cell D26). Do these values suggest that the Regression Equation you defined in Step 5 has good predictive power, or is there evidence of model overfitting? Provide your answer and justification in the third textbox, “Predictive Power of Regression”. Problem 2 – BlueOrRed Suppose that campaign organizers for both the Republican and Democratic parties are interested in identifying individual undecided voters who would consider voting for their party in an upcoming election. The file “Module 7 BlueOrRed Template.xlsx” contains data on a sample of voters with tracked variables, including whether or not they are undecided regarding their candidate preference, age, whether they own a home, gender, marital status, household size, income, years of education, and whether they attend church. Step 1: Open the Classify toolpack as in Problem 1 (make sure you do not open the Predict toolpack or your output will not match the descriptions below) and select k-Nearest Neighbors . On Page 1 of the k-Nearest Neighbors Classification settings, use Undecided as the Output Variable and Age, HomeOwner, Female, HouseholdSize, Income, Education, and Church (i.e. all the remaining variables except for Married) to the Selected Variables. Click Next. Step 2: On Page 2, select Partition Data, check the box next to Partition Data, and select Random Partition. Make sure that “User defined” partitions is activated, and accept the default 50/30/20 partitions. Choose Done. Step 3: Also on Page 2, click on Rescale Data, and in the dialogue box that opens, check the box next to Rescale Data. Confirm that “Standardization” is selected under Type, and click Done. Step 4: Still on Page 2, under Neighbors, set # Neighbors (K) to 10 and activate “Search 1..K” under Nearest Neighbors: Search. Step 5: Once more on Page 2, under the Advanced blue-bordered box, select and verify that the default option Empirical is active and click Done. Click Next > to proceed to Page 3. Step 6: On Page 3, check the box next to Lift Charts in the Score Test Data area. Make sure your dialog box matches the screenshot below, then click Finish. As was explained in Problem 1, this may take quite some time to complete and display. Step 7: Navigate to the new KNNC_Output worksheet and consider the Search Log beginning in cell B50. This table reports the misclassification percentage for each value of k, meaning for each number of neighbors used in the k-Nearest Neighbors Classification procedure. Based on which value for k has the smallest misclassification rate, what is the optimal number of neighbors to use in our analysis? Enter your response on the Data worksheet in cell L2. If your worksheet title instead reads KNNP_Output, you’ve run the Predict version of KNN rather than the Classify version, so you must delete these worksheets and return to Step 1. Step 8: Consider the Overall Error Rate reported on cell F21 of each Score Report (i.e. KNNC_TrainingScore, KNNC_ValidationScore, and KNNC_TestScore); does the error rate reported on the KNNC_Output seem to be optimistic (better than the true performance of the model), conservative (worse than the true performance of the model), or somewhere in the middle? Select your response from the drop-down menu on the Data worksheet in cell L4. Step 9: Navigate to the KNNC_TestLiftChart worksheet and consider the Decile Chart Data starting in cell I16. Based on this chart, after which decile does our model fail to improve our predictive power? I.e. which Decile is the last one to have a Lift above 1.0? Answer on the Data worksheet in cell L6. Problem 3 – CreditScore A consumer advocacy agency, Equitable Ernest, is interested in providing a service in which an individual can estimate their own credit score (a continuous measure used by banks, insurance companies, and other businesses when granting loans, quoting premiums, and issuing credit). The file “Module 7 CreditScore Template.xlsx” contains data on an individual’s credit score and other variables. Step 1: Use the Predict toolpack (Data Mining tab > Data Mining group) , and select the Regression Tree tool . Step 2: Select CreditScore as the Output Variable and all the other variables as the Selected Variables. Click Next to advance Page 2. Step 3: On Page 2, partition the data following the same process from the previous questions, allocating 40% to each of the Training and Validation Sets and 20% to the Test Set. Step 4: Also on Page 2, use the Rescale Data tool to Standardize the data. Step 5: Under Decision Tree: Fitting > Tree Growth, check the box next to Records in Terminal Nodes, and set the associated Limit Value to 244. Step 6: Under “Decision Tree: Model”, check the box next to “Prune (Using Validation Set)”, then select . In the “Select Tree for Scoring” dialogue box, activate the “Best Pruned” option. Choose Done. Step 7: Under Decision tree: Display > Tree Diagram, choose . In the “Select Trees to Display” dialogue box, check the boxes next to Fully Grown, Best Pruned, and Minimum Error. Step 8: Verify that your Regression Tree dialogue box matches the screenshot below, then push Next. Step 9: On Page 3, check the boxes to generate a Detailed Report for the Training, Validation, and Test Data sets, then click Finish (do not uncheck the Summary Report boxes). Step 10: Compare the RMSE values from each output worksheet RT_TrainingScore, RT_ValidationScore, and RT_TestScore, found on cell D15 on each sheet. Do these suggest that the pruned model has been overfit? Choose your response from the dropdown in the Data worksheet, cell L2, either “Yes” if you see evidence of overfitting, or “No” otherwise. Step 11: View the RT_BestTree worksheet; use the Parent and Child IDs to predict the credit score of an individual who has had 5 credit bureau inquiries, has used 10% of her available credit, has $14,500 of total available credit, has no collection reports or missed payments, is a homeowner, has an average credit age of 6.5 years, and has worked continuously for the past 5 years. Since we are using standardized values, we need to convert this information to the Standardized values, which to save you the effort are: -1.58 bureau inquiries, -1.77 credit usage, -0.46 total available credit, -0.31 collection reports, -0.69 missed payments, 0.73 homeowner, -0.44 average credit age, and -0.85 time on job. Be careful to pay attention to the sign of each number, and enter your answer in the blank in Data cell L4, rounding your answer to two (2) decimal places (or use a cell reference, if you prefer). Hint: the process for this was described in the Classification Trees video provided on D2L, and remember that if the value for the observation exceeds the Split Value, the observation continues down the right side of the tree. If the value is below the cutoff, then choose the left child. Final Submission Instructions Once you have completed all three problems above, submit your completed versions of each template to the Assignment on D2L, but you do not need to include this document, as your work should have been completed entirely in those workbooks. As always, let me know if you have any questions!
Data Customer Spending Card Coupon 1 2291 1 0 2 3215 1 0 3 2135 1 0 4 3924 0 0 5 2528 1 0 6 2473 0 1 7 2384 0 0 8 7076 0 0 9 1182 1 1 10 3345 0 0 11 2140 1 0 12 3255 0 1 13 1512 0 0 14 2148 0 1 15 6737 0 0 16 6486 0 0 17 1307 0 0 18 3470 1 0 19 2936 0 0 20 6404 0 1 21 2229 0 0 22 2933 0 0 23 2118 0 0 24 2050 0 0 25 4998 0 1 26 1394 0 0 27 3993 1 1 28 2059 0 1 29 1677 0 0 30 2229 0 1 31 1138 0 0 32 2933 1 0 33 5365 1 1 34 5365 0 0 35 6179 0 0 36 1980 1 0 37 1058 1 0 38 6851 1 1 39 1124 0 0 40 1911 0 0 41 3253 0 0 42 1839 0 0 43 1657 1 0 44 1075 0 0 45 3566 0 0 46 2118 0 0 47 1554 1 0 48 4631 0 0 49 4345 1 1 50 4004 1 1 51 1068 1 1 52 2421 0 0 53 4414 0 0 54 3386 1 1 55 1677 1 0 56 2050 1 1 57 2323 1 1 58 5501 0 0 59 3345 0 1 60 3318 1 1 61 4721 0 1 62 1662 0 1 63 2936 1 0 64 2049 0 0 65 2313 0 1 66 6851 0 0 67 2291 0 0 68 3470 1 1 69 3253 0 0 70 2059 0 0 71 2678 1 1 72 2323 1 0 73 1878 1 0 74 2678 1 1 75 6179 1 1 76 3411 1 1 77 5991 0 1 78 7076 1 1 79 3255 1 1 80 2148 1 0 81 5501 1 1 82 5991 1 1 83 2372 1 0 84 3995 1 0 85 2135 0 1 86 6737 1 1 87 6486 1 1 88 2429 1 0 89 4701 1 1 90 6404 1 0 91 1130 1 0 92 1911 1 1 93 4959 1 1 94 6073 1 1 95 1403 1 0 96 3318 0 0 97 2421 1 0 98 6073 0 0 99 2630 1 0 100 3411 0 1 101 3685 0 0 102 4914 0 0 103 1366 1 0 104 4787 0 0 105 2402 1 0 106 4173 1 1 107 1802 0 0 108 4971 0 0 109 2252 1 0 110 1979 1 0 111 6761 1 1 112 1786 1 0 113 5438 1 1 114 1834 0 0 115 2000 1 0 116 2366 0 0 117 968 1 0 118 2864 1 0 119 2246 1 0 120 8312 0 1 121 4005 1 1 122 1015 0 0 123 2180 0 0 124 2146 1 0 125 3276 1 0 126 5198 0 0 127 3508 1 1 128 3352 1 0 129 1409 1 0 130 3333 1 1 131 4207 1 1 132 4397 0 0 133 4494 1 0 134 3720 0 0 135 2793 0 0 136 17675 0 1 137 6474 1 1 138 1856 1 0 139 5257 1 1 140 3575 0 0 141 2277 0 0 142 1340 0 0 143 3004 0 0 144 2064 0 0 145 2815 1 0 146 2634 1 0 147 6930 0 0 148 7761 1 1 149 2719 1 0 150 5172 1 1 151 4073 0 0 152 2678 1 0 153 2609 0 0 154 5319 1 1 155 4281 0 0 156 2318 1 0 157 3195 0 0 158 7149 1 1 159 1982 0 0 160 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853 5059 1 0 854 2949 1 0 855 2130 1 0 856 5107 0 0 857 2490 1 0 858 1889 0 0 859 1176 1 0 860 1564 0 0 861 3576 1 0 862 6063 0 0 863 2681 0 0 864 1746 0 0 865 1282 1 0 866 2183 1 0 867 2995 1 0 868 3140 1 0 869 1540 1 0 870 7202 1 1 871 4265 1 1 872 5788 1 1 873 3095 0 0 874 4310 0 0 875 3892 0 0 876 2325 0 0 877 6390 0 0 878 2995 0 0 879 2291 1 0 880 3628 0 0 881 1995 1 0 882 2527 0 0 883 4953 0 0 884 2381 0 0 885 5216 0 0 886 6701 0 0 887 5284 1 1 888 3189 0 0 889 2403 1 0 890 2528 1 0 891 2955 0 0 892 2900 0 0 893 3488 1 0 894 1367 0 0 895 1311 1 0 896 1090 0 0 897 2407 1 0 898 2556 0 0 899 1302 1 0 900 4050 0 0 901 2503 0 0 902 3225 0 0 903 4384 0 0 904 2399 0 0 905 4369 0 0 906 3958 1 1 907 3730 1 0 908 4067 1 0 909 1492 0 0 910 3255 1 0 911 2906 0 0 912 3468 1 1 913 3781 0 0 914 1607 0 0 915 6244 1 1 916 2597 0 0 917 2114 0 0 918 1133 1 0 919 5281 1 1 920 2206 0 0 921 3626 0 0 922 5335 1 1 923 2192 0 0 924 2885 1 0 925 472 1 0 926 1603 1 0 927 2231 1 0 928 2965 1 0 929 1833 1 0 930 3268 1 1 931 2298 1 0 932 4417 1 0 933 2558 1 0 934 1512 1 0 935 992 0 0 936 2273 1 0 937 3755 0 0 938 4517 0 0 939 2186 0 0 940 3680 1 1 941 7521 0 1 942 4685 1 1 943 2949 1 0 944 2202 1 0 945 2254 1 0 946 2652 0 0 947 4336 0 0 948 2139 0 0 949 1794 1 0 950 5791 1 1 951 3072 0 0 952 4358 1 1 953 5148 1 1 954 3542 0 0 955 1552 0 0 956 2862 0 0 957 6225 1 1 958 6146 0 0 959 2474 1 0 960 708 0 0 961 6993 1 1 962 6113 1 1 963 2008 0 0 964 3359 0 0 965 2328 0 0 966 1710 0 0 967 4096 1 1 968 5900 1 1 969 7534 0 0 970 5041 1 1 971 1816 1 0 972 3867 0 0 973 1387 1 0 974 3514 1 0 975 5419 0 0 976 3368 1 0 977 2063 1 0 978 3006 0 0 979 2049 1 0 980 6512 1 1 981 2633 0 0 982 3277 0 0 983 2725 1 0 984 5498 1 1 985 2277 1 0 986 3700 1 0 987 2483 0 0 988 3420 0 0 989 3854 0 0 990 1655 1 0 991 1978 1 0 992 3214 1 0 993 3121 1 0 994 5708 0 0 995 1874 0 0 996 804 1 0 997 1936 0 0 998 3154 0 0 999 1970 1 0 1000 5816 1 1 Interpretation of Regression Equation The smallest classification error on the validation set results from the model: Interpretation of Lift Predictive Power of Regression
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