3.10 Training logistic regression with Scikit-Learn

3.10 Training logistic regression with Scikit-Learn

Slides

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.

• Notes from Peter Ernicke

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• Machine Learning Zoomcamp course
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