Introduction
This package contains functions for calculating various metrics relevant for learning to rank systems such as recommender systems.
IMPORTANT: This project is still in its very early stages. Results should be taken with a grain of salt.
scikit-learn-like APIs
This package aims to provide APIs that are familiar if you are used to working with scikit-learn.
Supported metrics
Recall@k
Bag Recall@k
Mean Rank Percentile
NDCG
1 maintainer
Metadata
1 maintainer
Release files for rankmetrics 1.0.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| rankmetrics-1.0.0.tar.gz | 4.8 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| rankmetrics-1.0.0-py2.py3-none-any.whl | Python 2, Python 3 | none | any | Details |
Total release size: 10.4 kB
Release files / rankmetrics-1.0.0.tar.gz
| Download URL | rankmetrics-1.0.0.tar.gz |
|---|---|
| Size | 4.8 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
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Release files / rankmetrics-1.0.0-py2.py3-none-any.whl
| Download URL | rankmetrics-1.0.0-py2.py3-none-any.whl |
|---|---|
| Size | 5.6 kB |
| Tags | Python 2 Python 3 |
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SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
