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I read the medium article linked in the "About" section here. I got the sample code running for confusion_matrix_plot(). I read the README.md as well. I still have the following questions.
What specifically is the "amount"? Amount of what? The amounts are all different (ex: [7.42079112e-01 9.20114688e-01 2.32900389e+00 ...]
I assume the "cost" is the cost of a false positive and cost of a false negative. If so, why are there multiple values for False Negative? I printed the entire "train_cost_dict" in your example and it gave: "'FN': array([9.97586566e-01, 1.51283561e+00, 6.72133633e-01, ...).
Typically, the cost of a false negative is one consistent value multiplied by the number of false negatives. In your example you set FNs to a range of values "FN = np.abs(X_train[:, 12])", why?
The False Positives make sense and are consistent. Your example set "FP = 10". When move the slider I see 2 FPs cost $20.
Thanks!
The text was updated successfully, but these errors were encountered:
Hi.
I read the medium article linked in the "About" section here. I got the sample code running for confusion_matrix_plot(). I read the README.md as well. I still have the following questions.
What specifically is the "amount"? Amount of what? The amounts are all different (ex: [7.42079112e-01 9.20114688e-01 2.32900389e+00 ...]
I assume the "cost" is the cost of a false positive and cost of a false negative. If so, why are there multiple values for False Negative? I printed the entire "train_cost_dict" in your example and it gave: "'FN': array([9.97586566e-01, 1.51283561e+00, 6.72133633e-01, ...).
Typically, the cost of a false negative is one consistent value multiplied by the number of false negatives. In your example you set FNs to a range of values "FN = np.abs(X_train[:, 12])", why?
The False Positives make sense and are consistent. Your example set "FP = 10". When move the slider I see 2 FPs cost $20.
Thanks!
The text was updated successfully, but these errors were encountered: