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A) Compute the ROC curve for this classifier and report the coordinates of the curve. To this end, use thresholding to turn the predicted values into the 0/1 classes and for each threshold, compute confusion matrices and the usual performance measures (FPR, TPR). The list of all these performance measures gives the coordinates of the curve. B) Compute the area under the curve and write it here AUC of this classifier. Briefly comment on the performance Q2 Classification A logistic classifier was fitted to data, and six fresh observations were used to assess the performance of this classifier. Here are the fitted logistic probabilities and the observations (Y values). ## Logistic predictions Fresh data values ## [1,] 0.90 0 ## [2,] 0.27 0 ## [3,] 0.37 0 ## [4,] 0.57 1 ## [5,] 0.93 1 ## [6,] 0.20 0

A) Compute the ROC curve for this classifier and report the coordinates of the curve. To this end, use thresholding to turn the predicted values into the 0/1 classes and for each threshold, compute confusion matrices and the usual performance measures (FPR, TPR). The list of all these performance measures gives the coordinates of the curve. B) Compute the area under the curve and write it here AUC of this classifier. Briefly comment on the performance Q2 Classification A logistic classifier was fitted to data, and six fresh observations were used to assess the performance of this classifier. Here are the fitted logistic probabilities and the observations (Y values). ## Logistic predictions Fresh data values ## [1,] 0.90 0 ## [2,] 0.27 0 ## [3,] 0.37 0 ## [4,] 0.57 1 ## [5,] 0.93 1 ## [6,] 0.20 0

Database System Concepts
Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
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A) Compute the ROC curve for this classifier and report the coordinates of the curve. To this end, use thresholding to turn the predicted values into the 0/1 classes and for each threshold, compute confusion matrices and the usual performance measures (FPR, TPR). The list of all these performance measures gives the coordinates of the curve. B) Compute the area under the curve and write it here AUC of this classifier. Briefly comment on the performance
Transcribed Image Text:A) Compute the ROC curve for this classifier and report the coordinates of the curve. To this end, use thresholding to turn the predicted values into the 0/1 classes and for each threshold, compute confusion matrices and the usual performance measures (FPR, TPR). The list of all these performance measures gives the coordinates of the curve. B) Compute the area under the curve and write it here AUC of this classifier. Briefly comment on the performance
Q2 Classification A logistic classifier was fitted to data, and six fresh observations were used to assess the performance of this classifier. Here are the fitted logistic probabilities and the observations (Y values). ## Logistic predictions Fresh data values ## [1,] 0.90 0 ## [2,] 0.27 0 ## [3,] 0.37 0 ## [4,] 0.57 1 ## [5,] 0.93 1 ## [6,] 0.20 0
Transcribed Image Text:Q2 Classification A logistic classifier was fitted to data, and six fresh observations were used to assess the performance of this classifier. Here are the fitted logistic probabilities and the observations (Y values). ## Logistic predictions Fresh data values ## [1,] 0.90 0 ## [2,] 0.27 0 ## [3,] 0.37 0 ## [4,] 0.57 1 ## [5,] 0.93 1 ## [6,] 0.20 0
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