Kaige Yang yang0110
yang0110
/ rank_metrics.py
Created
March 21, 2021 15:10
— 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 |
yang0110
/ graph-cluster.py
Created
July 16, 2017 22:24
— forked from cjdd3b/graph-cluster.py
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| ''' | |
| graph-cluster.py | |
| Some notes for doing graph clustering in a couple different ways: simple spectral | |
| partitioning based on the Fiedler vector, and a density-based clustering using DBSCAN. | |
| Why might this be useful? I'm using it to identify weakly connected (and therefore | |
| probably false) graph components in my campaign finance standardization workflow, the | |
| basic idea of which is here: https://github.com/cjdd3b/fec-standardizer/wiki |