Attribute sampling: Revision history

Diff selection: Mark the radio buttons of the revisions to compare and hit enter or the button at the bottom.
Legend: (cur) = difference with latest revision, (prev) = difference with preceding revision, m = minor edit.

17 March 2023

27 February 2023

  • curprev 18:0818:08, 27 February 2023‎ Alpha5 talk contribs‎ 7,172 bytes −26‎ No edit summary
  • curprev 18:0618:06, 27 February 2023‎ Alpha5 talk contribs‎ 7,198 bytes −1‎ No edit summary
  • curprev 18:0518:05, 27 February 2023‎ Alpha5 talk contribs‎ 7,199 bytes +7,199‎ Created page with "{{see also|Machine learning terms}} ===Attribute Sampling in Machine Learning== Attribute sampling is a technique in machine learning to randomly select some features from a dataset to train a model. This process can be done for various reasons, such as saving computational time during training, avoiding overfitting risks, and increasing model interpretability. In this article we'll examine different types of attribute sampling, their advantages and drawbacks, and when t..."
Retrieved from "http:///wiki/Attribute_sampling"