Tips on Scikit-Learn

Things on this page are fragmentary and immature notes/thoughts of the author. Please read with your own judgement!

1. Cross validation in scikit-learn supports pipeline in addition to vanilla models. Please refer to Cross Validation Pipeline for more details.

2. Label encoding is an easy way to convert a categorical response/target variable to a numeric one and back to the raw value space. For transform of response/target varible in regression, please refer to Transforming Target in Tegression.

3. Skorch

Metrics¶

• auc

• precision_recall_curve

• average_precision_score

References¶

https://scikit-learn.org/stable/modules/compose.html#transforming-target-in-regression

Split a Dataset into Train and Test Datasets in Python