Load information about a feature

What is feature selection for load forecasting?

Feature selection is the process of selecting a subset of relevant features for improving the computational efficiency and preventing overfitting in the model development. It is the data-driven approach for extracting automatically meaningful features and thus can provide a significant improvement in load forecasting.

How do I extract features from a dataset in Python?

The sklearn. feature_extraction module can be used to extract features in a format supported by machine learning algorithms from datasets consisting of formats such as text and image.



The latter is a machine learning technique applied on these features.

1. Loading features from dicts.
2. Feature hashing.
3. Text feature extraction.

What is the difference between feature extraction and feature selection?

What is feature extraction/selection? Straight to the point: Extraction: Getting useful features from existing data. Selection: Choosing a subset of the original pool of features.