Factorization Machines Study notes (i) Predictive tasks

Source: Internet
Author: User

     
    Recently learned an algorithm called Factorization Machines (FM), which can predict arbitrary real-valued vectors. The main advantages include: 1) can be used in highly sparse data scenarios, 2) with linear computational complexity. In this paper, the FM framework is briefly introduced, and its training algorithm-random gradient descent (SGD) method and alternating least squares (ALS) method are deduced in detail.

RELATED LINKS :

(i) Forecast tasks

(ii) Model equations

(iii) Return and classification

(iv) Learning algorithms





Author: peghoty

Source: http://blog.csdn.net/itplus/article/details/40534885

Welcome to reprint/share, but be sure to declare the source of the article.

Factorization Machines Study notes (i) Predictive tasks

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.