- Univariate Selection: In this method, we used SelectKBest Algo to find the feature score with respect to the dependent column.
- Extra Tree Classifier: This technique gives you a score for each feature of the data. The higher the score, the more important and relevant that feature is. You can import the class from sklean.ensemble.
- Correlation Matrix: A table that displays the correlation of all the features against each other. Each cell in the table displays a correlation between two variables. We can use a threshold value to select the less correlated variables out of the dataset.
- Mutual Information: It is a classifier that generates the mutual information of each feature with respect to the dependent feature. The higher the information is relevant it is.
“Torture the data, and it will confess to anything.”