An Approach to R Package Recommendation Engine
Slides presented by Alex to the NYC Predictive Analytics group on March 10, 2011 describing his approach to the R Package Recommendation Engine competition on Kaggle, where he placed 4th…
Presentation Outline
1. An Approach to R Package Recommendation Engine by Alex Lin of Intelligent Mining
2. Initial Thoughts
3. Steps
– Modified k-Nearest Neighbor algorithm.
– User average & package average as prior bias.
– User-specific package Maintainer Affinity.
– Matrix factorization (MF) to post-process the residuals.
– Other rules.
4. Modified k-Nearest Neighbor algorithm
5. User average and Package average as prior bias
6. User-specific Package Maintainer Affinity
7. So Far – baseline model
8. Matrix Factorization
9. Other Rules
10. Final Result
– Public AUC = 0.984914
– Final AUC = 0.979565
