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Examine the lift chart and the classification table for the tree. What can you say about the predictive performance of this model?       I have posted below my thoughts on the above charts Looking at the Lift Chart and the ROC Curve, the actual model performed better than the Naive model The decile chart seems to be skewed to the left. Based on the information from the classification summary we notice that the model didn’t do a great job at accurately predicting an auction as competitive or not competitive as it had an error rate average of 31.53% and an accuracy % of 68.82. The model more than often predicted the wrong class.

Examine the lift chart and the classification table for the tree. What can you say about the predictive performance of this model?       I have posted below my thoughts on the above charts Looking at the Lift Chart and the ROC Curve, the actual model performed better than the Naive model The decile chart seems to be skewed to the left. Based on the information from the classification summary we notice that the model didn’t do a great job at accurately predicting an auction as competitive or not competitive as it had an error rate average of 31.53% and an accuracy % of 68.82. The model more than often predicted the wrong class.

Computer Networking: A Top-Down Approach (7th Edition)
Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
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Problem R1RQ: What is the difference between a host and an end system? List several different types of end...
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Examine the lift chart and the classification table for the tree. What can you say about the predictive performance of this model?

 

 

 

I have posted below my thoughts on the above charts

  • Looking at the Lift Chart and the ROC Curve, the actual model performed better than the Naive model
  • The decile chart seems to be skewed to the left.
  • Based on the information from the classification summary we notice that the model didn’t do a great job at accurately predicting an auction as competitive or not competitive as it had an error rate average of 31.53% and an accuracy % of 68.82. The model more than often predicted the wrong class.
Lift Chart (Original) ROC Curve, AUC=0.71934472457572562 Lift Chart (Oniginal) Random Classifier Optimum Classifier Fitted Classifier 1.0 Cumulative actual when sorted using predicted values 0.9- 650 0.8- 600 - 550- 0.7- 500 - 450 - 0.6 400- 0.5- 350 - 0.4 - 300 - 250 - 0.3 200- 150 - 0.2 - 100 - 0.1 S0- 0- 100 200 300 400 so0 600 700 B00 900 1,000,100 0.0 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 * Cases 1-specificity Decile-wise Lift Chart Validation: Classification Summary 1.67 Confusion Matrix Actual Predicted -0 1.4- 257 126 120 1 286, 1.2 - Error Report # Cases - Errors - Error 120 31 83024 126 30.58252 246 31.17871, 1.0- Class 377 1 Overall 0.0 412 789 0.6 Metrics Metric Accuracy Wcorrect Accuracy (icorrect) 68.821293 Specificity Sensitivity (Recall) 0.6941748 Precision Value 543 0.4- 0.2- 0.6816976 0.0+ 8 9 0.7044335 1 10 F1 score Success Class Success Probability Declle 0.6992665 1 05 Declle/Global Mean Cumulative Sensitivity
Transcribed Image Text:Lift Chart (Original) ROC Curve, AUC=0.71934472457572562 Lift Chart (Oniginal) Random Classifier Optimum Classifier Fitted Classifier 1.0 Cumulative actual when sorted using predicted values 0.9- 650 0.8- 600 - 550- 0.7- 500 - 450 - 0.6 400- 0.5- 350 - 0.4 - 300 - 250 - 0.3 200- 150 - 0.2 - 100 - 0.1 S0- 0- 100 200 300 400 so0 600 700 B00 900 1,000,100 0.0 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 * Cases 1-specificity Decile-wise Lift Chart Validation: Classification Summary 1.67 Confusion Matrix Actual Predicted -0 1.4- 257 126 120 1 286, 1.2 - Error Report # Cases - Errors - Error 120 31 83024 126 30.58252 246 31.17871, 1.0- Class 377 1 Overall 0.0 412 789 0.6 Metrics Metric Accuracy Wcorrect Accuracy (icorrect) 68.821293 Specificity Sensitivity (Recall) 0.6941748 Precision Value 543 0.4- 0.2- 0.6816976 0.0+ 8 9 0.7044335 1 10 F1 score Success Class Success Probability Declle 0.6992665 1 05 Declle/Global Mean Cumulative Sensitivity
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