pyDML
pypi i pyDML

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pypi i pyDML

# pyDML

Distance Metric Learning Algorithms for Python

## What is Distance Metric Learning?

Many machine learning algorithms need a similarity measure to carry out their tasks. Usually, standard distances, like euclidean distance, are used to measure this similarity. Distance Metric Learning algorithms try to learn an optimal distance from the data.

## How to learn a distance?

There are two main ways to learn a distance in Distance Metric Learning:

Every linear map defines a single metric (M = L'L), and two linear maps that define the same metric only differ in an isometry. So both approaches are equivalent.

## Some applications

### Improve distance based classifiers

Improving 1-NN classification.

### Dimensionality reduction

Learning a projection onto a plane for the digits dataset (dimension 64).

## Documentation

See the available algorithms, the additional functionalities and the full documentation here.

## Stats

The distance metric learning algorithms in pyDML are being evaluated in several datasets. The results of these experiments are available in the pyDML-Stats repository.

## Installation

• From GitHub: clone or download this repository and run the command python setup.py install on the root directory.

## Authors

124

1yr ago

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### OPEN PRs

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0.1.0
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0.0.1
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0.0.1b0
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