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Training logistic regression with Scikit-Learn — Machine Learning Zoomcamp Module 3

This video was about training a logistic regression model with Scikit-Learn, applying it to the validation dataset, and calculating its accuracy.

mlz-module-03

Notes

This video was about training a logistic regression model with Scikit-Learn, applying it to the validation dataset, and calculating its accuracy.

Classes, functions, and methods:

LogisticRegression().fit(x) - Scikit-Learn class for training the logistic regression model.
LogisticRegression().coef_[0] - return the coefficients or weights of the LR model
LogisticRegression().intercept_[0] - return the bias or intercept of the LR model
LogisticRegression().predict[x] - make predictions on the x dataset
LogisticRegression().predict_proba[x] - make predictions on the x dataset by returning two columns with their probabilities for the two categories - soft predictions

The entire code of this project is available in this jupyter notebook.

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