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Andrew Hershy
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Andrew Hershy

Andrew Hershy

Jul 8, 2019·1 min read

You’re right, the brier score would be a good addition to this.

I used sklearn. metrics.brier_score_loss() to calculate the score on both logistic and random forest results:

from sklearn.metrics import brier_score_loss as bsl#logistic regression
bsl(y_test_1,y_1_prob)
Out: 0.181#random forest
bsl(y_test,y_1_prob)
Out: 0.215

Logistic regression wins here also.

Andrew Hershy

LinkedIn:https://www.linkedin.com/in/andrew-hershy-a7779199/

You have to use a test set and brier score.
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