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update README_pypi
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enriquegit committed Mar 5, 2024
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10 changes: 6 additions & 4 deletions README_pypi.md
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# multiviewstacking: a python implementation of the Multi-View Stacking algorithm.
# multiviewstacking: a python implementation of the Multi-View Stacking algorithm <img src="https://github.com/enriquegit/multiviewstacking/blob/main/img/logo60-50.png?raw=true" align="right" width="300px " alt=""/>



Multi-View learning algorithms aim to learn from different representational views. For example, a movie can be represented by three views. The sequence of images, the audio, and the subtitles. Instead of concatenating the features of every view and training a single model, the Multi-View Stacking algorithm[1] builds independent (and possibly of different types) models for each view. These models are called *first-level-learners*. Then, the class and score predictions of the first-level-learners are used as features to train another model called the *meta-learner*. This approach is based on the Stacked Generalization method proposed by Wolpert D. H.[2].

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* Combine different types of first-level-learners.
* Comes with a pre-loaded dataset with two views for testing.

## :clipboard: Requirements
## Requirements

- Python 3.8+
- pandas
- numpy
- scikit-learn >= 1.2.2

## :wrench: Installation
## Installation

You can install the `multiviewstacking` package with:

```
pip install multiviewstacking
```

## :rocket: Quick start example
## Quick start example

This quick start example shows you how to train a multi-view model. For more detailed tutorials, check the jupyter notebooks in the [/examples](https://github.com/enriquegit/multiviewstacking/tree/main/examples) directory.

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2 changes: 1 addition & 1 deletion setup.py
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setup(
name='multiviewstacking',
version='0.0.3',
version='0.0.5',
description = 'Python implementation of the Multi-View Stacking algorithm.',
long_description = long_description,
long_description_content_type = 'text/markdown',
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