Skip to content

Latest commit

 

History

History
40 lines (27 loc) · 1.71 KB

10-training-log-reg.md

File metadata and controls

40 lines (27 loc) · 1.71 KB
Raw

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.

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

Navigation