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Model Evaluation

Model Evaluation. Saed Sayad. Data Mining Steps. Model Evaluation. Classification - Confusion Matrix. Positive Cases. Negative Cases. Predicted Positive. Predicted Negative. Confusion Matrix - Evaluation Measurements. Actual. Predicted. Sensitivity and Specificity.

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Model Evaluation

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  1. Model Evaluation Saed Sayad www.ismartsoft.com

  2. Data Mining Steps www.ismartsoft.com

  3. Model Evaluation www.ismartsoft.com

  4. Classification - Confusion Matrix Positive Cases Negative Cases Predicted Positive Predicted Negative www.ismartsoft.com

  5. Confusion Matrix -Evaluation Measurements Actual Predicted

  6. Sensitivity and Specificity www.ismartsoft.com

  7. Classification – Gain Chart Target% Wizard 100% Model Random Population% 0% 50% 100% www.ismartsoft.com

  8. Gain Chart Target% Wizard 100% A 50% Random 10% Population% 10% 18% 50% 100% www.ismartsoft.com

  9. Gain Chart Score Table Sorted by Score Gain Table www.ismartsoft.com

  10. Classification – Gain Chart Target% 100% A 85% 76% B 66% 54% 36% Population% 10% 20% 30% 40% 50% 100% www.ismartsoft.com

  11. Lift Chart Lift Table Gain Table www.ismartsoft.com

  12. Lift Chart Lift Population% www.ismartsoft.com

  13. K-S Chart (Kolmogorov-Smirnov) K-S K(0.95) = 6.0%    K(0.99) = 7.1%  www.ismartsoft.com

  14. K-S Chart Count% Score www.ismartsoft.com

  15. ROC Chart(Receiver Operating Characteristic) www.ismartsoft.com

  16. ROC Chart Sensitivity 1-Specificity www.ismartsoft.com

  17. Regression – Mean Squared Error www.ismartsoft.com

  18. Regression – Relative Squared Error www.ismartsoft.com

  19. Regression – Mean Absolute Error www.ismartsoft.com

  20. Regression – Relative Absolute Error www.ismartsoft.com

  21. Regression – Standardized Residuals Plot www.ismartsoft.com

  22. Questions? www.ismartsoft.com

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