Supervised Collaborative Filtering Based on Ridge Alternating Least Squares and Iterative Projection Pursuit
This paper presents a supervised data imputation based on the class-dependent matrix factors, which are generated during matrix factorization. The proposed ridge alternating least squares imputation uses class information to create substituted values, which approximate the characteristics of their c...
Main Authors: | , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2017-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/7888956/ |