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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_transform(x) - Scikit-Learn class for calculating the logistic regression model.
  • LogisticRegression().coef_[0] - returns the coeffcients or weights of the LR model
  • LogisticRegression().intercept_[0] - returns 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, and returns two columns with their probabilities for the two categories - soft predictions

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

⚠️ The notes are written by the community.
If you see an error here, please create a PR with a fix.

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