A sports betting company is testing the effectiveness of its online ads and has developed a classification model that predicts whether a potential customer will respond to its offer using information in the potential customer's browser history (cookies, etc.). Out of a test dataset of 1,000 customers, the 100 customers most likely to respond (according to the model) are identified and it is discovered that 14 of these actually did respond to the online ads. In the entire test dataset of 1,000 customers, only 39 customers responded to the ad. What is the lift of the classification model for the set of 100 customers it identified as most likely to respond? If required, round your answer to two decimal places. I got 3.59 as the answer and its incorrect.
A sports betting company is testing the effectiveness of its online ads and has developed a classification model that predicts whether a potential customer will respond to its offer using information in the potential customer's browser history (cookies, etc.). Out of a test dataset of 1,000 customers, the 100 customers most likely to respond (according to the model) are identified and it is discovered that 14 of these actually did respond to the online ads. In the entire test dataset of 1,000 customers, only 39 customers responded to the ad. What is the lift of the classification model for the set of 100 customers it identified as most likely to respond? If required, round your answer to two decimal places.
I got 3.59 as the answer and its incorrect.
Trending now
This is a popular solution!
Step by step
Solved in 3 steps with 10 images
