Aug 4, 2014 · Scikit-learn deliberately does not support statistical inference. If you want out-of-the-box coefficients significance tests (and much more), you can use Logit estimator from …

82 I have a binary prediction model trained by logistic regression algorithm. I want know which features (predictors) are more important for the decision of positive or negative class. I know …

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Note that if you use an iterative optimization of least-squares with your custom loss function (i.e., rather than using the pseudo-inverse algorithm), then you may be able to trim the model …

Jun 19, 2020 · 3 For most models in scikit-learn, we can get the probability estimates for the classes through predict_proba. Bear in mind that this is the actual output of the logistic …

Jan 3, 2014 · In current version of scikit-learn, LogisticRegression() now has n_jobs parameter to utilize multiple cores. However, the actual text of the user guide suggests that multiple cores …

Jun 10, 2021 · It cannot learn a true multinomial (multiclass) model; instead, the optimization problem is decomposed in a “one-vs-rest” fashion, so separate binary classifiers are trained …

May 13, 2021 · scikit-learn's LogisticRegression regularizes by default (?!) If we circle back to scikit-learn, as mentioned earlier, because coefficients become smaller with regularization, it is …

Nov 29, 2019 · python machine-learning scikit-learn logistic-regression asked Nov 29, 2019 at 23:38 Rohan Dsouza 111 2 2 5

Jun 22, 2015 · I am having a lot of trouble understanding how the class_weight parameter in scikit-learn's Logistic Regression operates. The Situation I want to use logistic regression to …