We have built a prediction model to predict if a person will buy a computer or...

 

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We have built a prediction model to predict if a person will buy a computer or not. To evaluate the model, we have a list of 100 people with some basic attributes (e.g., age, student status, income, credit rating) and an attribute specifying if he/she actually bought a computer or not. The following table shows the details of the evaluation results. Please answer the following questions (use the definition of F1-score reported here below): Predicted to buy a computer Predicted not to buy a computer F = 2* True Positive = Actually bought a computer Actually did not buy a computer precision * recall precision + recall False Positive = True Negative = False Negative = F1 = 45 20 10 25 We have built a prediction model to predict if a person will buy a computer or not. To evaluate the model, we have a list of 100 people with some basic attributes (e.g., age, student status, income, credit rating) and an attribute specifying if he/she actually bought a computer or not. The following table shows the details of the evaluation results. Please answer the following questions (use the definition of F1-score reported here below): Predicted to buy a computer Predicted not to buy a computer F = 2* True Positive = Actually bought a computer Actually did not buy a computer precision * recall precision + recall False Positive = True Negative = False Negative = F1 = 45 20 10 25

Answer rating: 100% (QA)

Actually bought a computer ... View the full answer