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2 votes

How sklearn logistic regression computes accuracy, recall etc if we don't provide threshold?

The default threshold is 0.5, so it is computed on that basis. It is kind of a problem as it isn't well documented (not even on the logistic regression predict page) and a very common pitfall. The two ...
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0 votes

Decision tree vs logistic regression feature importances

The difference in the importance of the 'Total day charge' coefficient between the decision tree and logistic regression models is due to the way that each model ...
  • 2,981
0 votes

Why does Logistic Regression perform better than machine learning models in clinical prediction studies

Clinical trial data is typically collected from a sample population and often has a limited size and number of features. Complex models applied to such data are more likely to overfit, whereas simpler ...
  • 93
0 votes

Why is my predictor value (continuous) perfectly correlated with my logit value (when testing logistic regression model assumptions)?

$$ \text{logit}=\hat\beta_0+\hat\beta_1x\\ \text{cor}(x, \text{logit})\\ =\text{cor}(x, \hat\beta_0+\hat\beta_1x)\\ =\text{cor}(x, \hat\beta_1x) $$ If the estimated slope coefficient $\hat\beta_1>0$...
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