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E123502191 N954020003 M965040023

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Introduction 79

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Introduction

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Introduction

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Determination of data set

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Data mining procedure Berry Linoff 10 10

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Step 1. Translate the business problem into a data mining problem

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Step 2. Select appropriate data 4117

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Step 3. Get to know the data ID m/f single/married/divsepwid weekly/monthly y/n good risk bad risk bad profit

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Step4. create a model set 4117 6 4 2455 1662 Overfitting

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Step5. fix problems with the data 4117

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Step5. fix problems with the data ( )

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Step6. transform data to bring information to the surface

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Step6. transform data to bring information to the surface

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Step7. Build models (Decision Tree)

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Step7. Build models (Neural Network)

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Step7. Build models (Logistic)

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Step8. Assess models 1662

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Correct1,87776.46% Wrong57823.54% Total2,455 Correct1,20472.44% Wrong45827.56% Total1,662

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- training bad lossbad profitgood risk bad loss Count31117474 Row %55.6431.1313.24 Total %12.677.093.01 bad profit Count84131774 Row %5.6989.295.02 Total %3.4253.653.01 good risk Count43129249 Row %10.2130.6459.14 Total %1.755.2510.14

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- testing bad lossbad profitgood risk bad loss Count18113135 Row %52.1637.7510.09 Total %10.897.882.11 bad profit Count7582631 Row %8.0588.633.33 Total %4.5149.71.87 good risk Count40146197 Row %10.4438.1251.44 Total %2.418.7811.85

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1662

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Correct1,78772.79% Wrong66827.21% Total2,455 Correct1,31479.06% Wrong34820.94% Total1,662

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- training bad lossbad profitgood risk bad loss Count19127692 Row %34.1749.3716.46 Total %7.7811.243.75 bad profit Count251334116 Row %1.6990.447.86 Total %1.0254.344.73 good risk Count6153262 Row %1.4336.3462.23 Total %0.246.2310.67

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- testing bad lossbad profitgood risk bad loss Count14717426 Row %42.3650.147.49 Total %8.8410.471.56 bad profit Count1490315 Row %1.596.891.61 Total %0.8454.330.9 good risk Count10109264 Row %2.6128.4668.93 Total %0.66.5615.88

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1662

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Correct1,74070.88% Wrong71529.12% Total2,455 Correct1,22973.95% Wrong43326.05% Total1,662

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- training bad lossbad profitgood risk bad loss Count23325472 Row %41.6845.4412.88 Total %9.4910.352.93 bad profit Count91130579 Row %6.1788.475.36 Total %3.7153.163.22 good risk Count37182202 Row %8.7943.2347.98 Total %1.517.418.23

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- testing bad lossbad profitgood risk bad loss Count17715020 Row %51.0143.235.76 Total %10.659.031.2 bad profit Count578678 Row %6.1293.030.86 Total %3.4352.170.48 good risk Count32166185 Row %8.3643.3448.3 Total %1.939.9911.13

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Step9. Deploy models 1204 72.44

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1314 79.06 0.333 0.209 0.207 0.187 0.158 0.156 0.05 0.048 0.046

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1662 1229 73.95 Equation For good risk 0.01426 * + 0.00001368 * 0.324 * 0.4787 * 0.3575 * 0.1567 * [ =f] + 5.251 * [ =divsepwid] 0.0184 * [ =married] + 0.8561 * [ =monthly] 0.3472 * [ =n] + 1.572 * [ =0] + 1.314 * [ =1] 0.01788 * [ =2] 0.1962 Equation For bad profit 0.06256 * 0.00002478 * 0.1728 * 0.416 * 0.4008 * + 0.1433 * [ =f] + 2.158 * [ =divsepwid] 0.348 * [ =married] 0.01668 * [ =monthly] + 0.0883 * [ =n] 1.382 * [ =0] + 0.4091 * [ =1] + 0.2016 * [ =2] + 5.602

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Step10 Assess results bad risk > good risk 3.01 >2.11 3.15 1.56 2.93 1.2

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Conclusion 1. - 2. bad loss good risk 3.

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Limit 1. 2.