Metadata-Version: 2.3
Name: mimllearning
Version: 0.5.13
Summary: MIML Learning Library
Project-URL: Homepage, https://github.com/p82maavd/miml
Author-email: Damian Martinez <damianmartinezavila@gmail.com>
License-Expression: GPL-3.0
License-File: LICENSE.txt
Keywords: data-science,machine-learning,miml,multi-instance,multilabel,python
Classifier: License :: OSI Approved :: GNU General Public License v3 or later (GPLv3+)
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Requires-Python: >=3.8
Description-Content-Type: text/markdown

# miml: Multi Instance Multi Label Learning Library for Python
The aim of the library is to ease the development, testing and comparison of classification algorithms for multi-instance multi-label learning (MIML). 

## Table of Contents

- [Installation](#installation)
- [Usage](#usage)
- [License](#license)

### Installation

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install miml.

```bash
$ pip install mimllearning
```
#### Requirements
The requirement packages for miml library are: numpy and scikit-learn.
Installing miml with the package manager does not install the package dependencies.
So install them with the package manager manually if not already downloaded.

    $ pip install numpy
    $ pip install scikit-learn

### Usage


#### Datasets

``` python
import pkg_resources
from miml.data.load_datasets import load_dataset

dataset_train = load_dataset(pkg_resources.resource_filename('miml', 'datasets/miml_birds_random_80train.arff'),
                             delimiter="'")
dataset_test = load_dataset(pkg_resources.resource_filename('miml', 'datasets/miml_birds_random_20test.arff'),
                            delimiter="'")
```

#### Classifier

``` python
from miml.classifier import MIMLtoMIBRClassifier, AllPositiveAPRClassifier

classifier_mi = MIMLtoMIBRClassifier(AllPositiveAPRClassifier())
classifier_mi.fit(dataset_train)
results_mi=classifier_mi.evaluate(dataset_test)
```

#### Report

``` python
from miml.report import Report

report = Report()
report.to_string(dataset_test.get_labels_by_bag(), results_ml)
print("")
report.to_csv(dataset_test.get_labels_by_bag(), results_ml)
```

### License
MIML library is released under the GNU General Public License [GPLv3](https://www.gnu.org/licenses/gpl-3.0.html).
