KSU Compression Algorithm Implementation
Algortihm 1 from Nearest-Neighbor Sample Compression: Efficiency, Consistency, Infinite Dimensions
Installation
- With pip:
pip install ksu - From source:
git clone --recursive https://github.com/nimroha/ksu_classifier.gitcd ksu_classifierpython setup.py install
Usage
This package provides a class KSU(Xs, Ys, metric, [gramPath, prune])
Xs and Ys are the data points and their respective labels as numpy arrays
metric is either a callable to compute the metric or a string that names one of our provided metrics (print ksu.KSU.METRICS.keys() for the full list)
gramPath (optional, default=None) a path to a precomputed gramian matrix
prune (optional, default=False) a boolean indicating whether to prune the compressed set or not (Algorithm 2 from Near-optimal sample compression for nearest neighbors)
KSU provides a method makePredictor([delta])
Which returns a 1-NN Classifer (based on sklearn's K-NN) fitted to the compressed data, where delta (optional, default=5%) is the required confidence of said classifier.
1 maintainer
Metadata
1 maintainer
Release files for ksu 0.1.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
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| ksu-0.1.2.tar.gz | 8.4 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| ksu-0.1.2-py2.py3-none-any.whl | Python 2, Python 3 | none | any | Details |
Total release size: 17.0 kB
Release files / ksu-0.1.2.tar.gz
| Download URL | ksu-0.1.2.tar.gz |
|---|---|
| Size | 8.4 kB |
| Tags | Source |
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Release files / ksu-0.1.2-py2.py3-none-any.whl
| Download URL | ksu-0.1.2-py2.py3-none-any.whl |
|---|---|
| Size | 8.7 kB |
| Tags | Python 2 Python 3 |
|
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