this exercise we will use code that we already have. Use the fucntion you created to compute the precision of a model, remember that the precision of a model is:$precision=(tp/(tp+fp))$ where tp is the number of true positives and fp is the number of false positives. The file performance.txt has data from models that were used in an experiment, the data has the model id, number of true positives and number of false positives for each model. Remember again that the model is good if its precision is above 0.75.\n", "\n", "Open the file, read each model and print if the model is good or bad. At the end, print the id of the best model and its precision. Be sure to use a function to compute the precision of each model."

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
Problem 1PE
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"In this exercise we will use code that we already have. Use the fucntion you created to compute the precision of a model, remember that the precision of a model is:$precision=(tp/(tp+fp))$ where tp is the number of true positives and fp is the number of false positives. The file performance.txt has data from models that were used in an experiment, the data has the model id, number of true positives and number of false positives for each model. Remember again that the model is good if its precision is above 0.75.\n", "\n", "Open the file, read each model and print if the model is good or bad. At the end, print the id of the best model and its precision. Be sure to use a function to compute the precision of each model."

al2 78 23
85 37
b27
b32
31 80
a19 67 14
x34 92 43
x42 87 21
212 54 32
x54 75 30
257 89 21
aa2 42 17
Transcribed Image Text:al2 78 23 85 37 b27 b32 31 80 a19 67 14 x34 92 43 x42 87 21 212 54 32 x54 75 30 257 89 21 aa2 42 17
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