NaumanAnwar97 / Feature-Selection Public

Notifications You must be signed in to change notification settings
Fork 0
Star 0

Feature Selection Using Python (Forward Selection and Backward Elimination)

0 stars 0 forks Branches Tags Activity

Notifications

Name		Name	Last commit message	Last commit date
Latest commit History 10 Commits
.gitignore		.gitignore
FeatureSelection.ipynb		FeatureSelection.ipynb
README.md		README.md
sample_submission.csv		sample_submission.csv
test.csv		test.csv
train.csv		train.csv

Repository files navigation

Feature-Selection

Forward selection is an iterative method in which we start with having no feature in the model. In each iteration, we keep adding the feature that best improves our model till the addition of a new variable does not improve the performance of the model.

Backward elimination is a feature selection technique while building a machine learning model. It is used to remove those features that do not have a significant effect on the dependent variable or prediction of output.

About

Feature Selection Using Python (Forward Selection and Backward Elimination)

python feature-selection feature-extraction unsupervised-learning forward-selection backward-elimination wrapper-methods

Report repository

Releases

No releases published

Packages

No packages published

Languages

Jupyter Notebook 100.0%