Why is it possible to have a fit, and what methods can be used to prevent or overcome overfitting

Source: Internet
Author: User
Why are there any methods that can prevent or overcome overfitting?
What is overfitting:

The so-called overfitting (Overfit) is a phenomenon in which a hypothesis can be better fitted to the training data than other assumptions, but not well fitted to data sets outside of the training data. At this point we call this hypothesis that there is a overfit phenomenon.


Reasons for overfitting:

The main reason for this is that there is noise in the training data or too little training data.


Measures to prevent or overcome:1 . Increase the amount of data
2, reduce the number of feature (manual definition of how many feature or algorithm to choose these feature)
3, regularization (leaving all the feature, but for the partial feature definition of its parameter very small)
4. Cross-validation

Why is it possible to have a fit, and what methods can be used to prevent or overcome overfitting

Contact Us

The content source of this page is from Internet, which doesn't represent Alibaba Cloud's opinion; products and services mentioned on that page don't have any relationship with Alibaba Cloud. If the content of the page makes you feel confusing, please write us an email, we will handle the problem within 5 days after receiving your email.

If you find any instances of plagiarism from the community, please send an email to: info-contact@alibabacloud.com and provide relevant evidence. A staff member will contact you within 5 working days.

A Free Trial That Lets You Build Big!

Start building with 50+ products and up to 12 months usage for Elastic Compute Service

  • Sales Support

    1 on 1 presale consultation

  • After-Sales Support

    24/7 Technical Support 6 Free Tickets per Quarter Faster Response

  • Alibaba Cloud offers highly flexible support services tailored to meet your exact needs.