scikit learn - How to get p-value and confident interval in ...
Nov 29, 2016 · 32 I am building a multinomial logistic regression with sklearn (LogisticRegression). But after it finishes, how can I get a p-value and confident interval of my …
scikit learn - Logistic regression does cannot converge without …
Jul 16, 2020 · I have a multi-class classification logistic regression model. Using a very basic sklearn pipeline I am taking in cleansed text descriptions of an object and classifying said …
feature names in LogisticRegression () - Data Science Stack Exchange
Mar 15, 2018 · We if you're using sklearn's LogisticRegression, then it's the same order as the column names appear in the training data. see below code. from sklearn.linear_model import …
python - Difference between sklearn's LogisticRegression and ...
Nov 24, 2022 · What is the difference between sklearn's LogisticRegression classifier and its SGDClassifier? I understand that the SGD is an optimization method, while Logistic …
Does scikit-learn have a forward selection/stepwise regression ...
Apr 27, 2017 · Sklearn DOES have a forward selection algorithm, although it isn't called that in scikit-learn. The feature selection method called F_regression in scikit-learn will sequentially …
Scikit-learn: Getting SGDClassifier to predict as well as a Logistic ...
Aug 4, 2015 · A way to train a Logistic Regression is by using stochastic gradient descent, which scikit-learn offers an interface to. What I would like to do is take a scikit-learn's SGDClassifier …
Logistic Regression using Logisticregression () class
Oct 5, 2022 · In the documentation of Logisticregression() offered by sklearn library, it states the following note: The underlying C implementation uses a random number generator to select …
Multinomial Logistic Regression sensitive to choice of Encoding
Feb 1, 2024 · Linear models (like logistic regression) perform poorly, so you should try decision trees (especially random forests, gradient boosting) which will mostly use the encoding implied …
Dealing with NaN (missing) values for Logistic Regression- Best …
The calculations can be performed smoothly if I replace all NaN values with 1 or 0. However I am not sure if that is the best way to deal with this issue, and I was also wondering what …
How to interpret my logistic regression result with statsmodels
Jan 17, 2021 · 1 so I'am doing a logistic regression with statsmodels and sklearn. My result confuses me a bit. I used a feature selection algorithm in my previous step, which tells me to …