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 chartsLooking at the Lift Chart and the ROC Curve, the actual model performed better than the Naive modelThe 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=0.71934472457572562Lift Chart (Oniginal)Random ClassifierOptimum ClassifierFitted Classifier1.0Cumulative actual when sorted using predicted values0.9-6500.8-600 -550-0.7-500 -450 -0.6400-0.5-350 -0.4 -300 -250 -0.3200-150 -0.2 -100 -0.1S0-0-100 200 300 400 so0 600 700 B00 900 1,000,1000.00.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0* Cases1-specificityDecile-wise Lift ChartValidation: Classification Summary1.67Confusion MatrixActual Predicted -01.4-2571261201286,1.2 -Error Report# Cases - Errors - Error120 31 83024126 30.58252246 31.17871,1.0-Class3771Overall0.04127890.6MetricsMetricAccuracy WcorrectAccuracy (icorrect) 68.821293SpecificitySensitivity (Recall) 0.6941748PrecisionValue5430.4-0.2-0.68169760.0+8 90.7044335110F1 scoreSuccess ClassSuccess ProbabilityDeclle0.6992665105Declle/Global MeanCumulativeSensitivity

The x-pivot of the diagram addresses the level of the test dataset that is utilized to analyze the…

Answered: Examine the lift chart and the…

7th Edition

ISBN:9780133594140

Author:James Kurose, Keith Ross

Publisher:James Kurose, Keith Ross

Chapter1: Computer Networks And The Internet

Section: Chapter Questions

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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.