morningsky
/ rank_metrics.py
Created
April 15, 2017 07:06
— forked from bwhite/rank_metrics.py
Ranking Metrics
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| """Information Retrieval metrics | |
| Useful Resources: | |
| http://www.cs.utexas.edu/~mooney/ir-course/slides/Evaluation.ppt | |
| http://www.nii.ac.jp/TechReports/05-014E.pdf | |
| http://www.stanford.edu/class/cs276/handouts/EvaluationNew-handout-6-per.pdf | |
| http://hal.archives-ouvertes.fr/docs/00/72/67/60/PDF/07-busa-fekete.pdf | |
| Learning to Rank for Information Retrieval (Tie-Yan Liu) | |
| """ | |
| import numpy as np |
morningsky
/ ranking.py
Created
June 15, 2017 18:34
— forked from agramfort/ranking.py
Pairwise ranking using scikit-learn LinearSVC
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| """ | |
| Implementation of pairwise ranking using scikit-learn LinearSVC | |
| Reference: "Large Margin Rank Boundaries for Ordinal Regression", R. Herbrich, | |
| T. Graepel, K. Obermayer. | |
| Authors: Fabian Pedregosa <fabian@fseoane.net> | |
| Alexandre Gramfort <alexandre.gramfort@inria.fr> | |
| """ |