diff --git a/ChangeLog.md b/ChangeLog.md index e2ea192..fab8c34 100644 --- a/ChangeLog.md +++ b/ChangeLog.md @@ -1,6 +1,13 @@ +# Version 0.1.5 + ++ Add more regression and classification datasets ++ Update documents, examples, test ++ Remove matplotlib dependency + +--------------------------------------------------------------------- + # Version 0.1.4 -+ Relocate regression and classification datasets + Add Unsupervised-based methods: - "VAR": Variance Threshold method - "MAD": Mean Absolute Difference diff --git a/README.md b/README.md index 3458cb6..725e549 100644 --- a/README.md +++ b/README.md @@ -4,7 +4,7 @@ --- -[![GitHub release](https://img.shields.io/badge/release-0.1.4-yellow.svg)](https://github.com/thieu1995/mafese/releases) +[![GitHub release](https://img.shields.io/badge/release-0.1.5-yellow.svg)](https://github.com/thieu1995/mafese/releases) [![Wheel](https://img.shields.io/pypi/wheel/gensim.svg)](https://pypi.python.org/pypi/mafese) [![PyPI version](https://badge.fury.io/py/mafese.svg)](https://badge.fury.io/py/mafese) ![PyPI - Python Version](https://img.shields.io/pypi/pyversions/mafese.svg) @@ -21,7 +21,7 @@ [![License: GPL v3](https://img.shields.io/badge/License-GPLv3-blue.svg)](https://www.gnu.org/licenses/gpl-3.0) -MAFESE (Metaheuristic Algorithms for FEature SElection) is the largest python library focused on feature selection +MAFESE (Metaheuristic Algorithms for FEature SElection) is the largest python library for feature selection problem using meta-heuristic algorithms. * **Free software:** GNU General Public License (GPL) V3 license @@ -30,7 +30,7 @@ using meta-heuristic algorithms. * **Total Embedded-based (Tree and Lasso)**: > 10 methods * **Total Unsupervised-based**: >= 4 methods * **Total classification dataset**: >= 30 datasets -* **Total regression dataset**: >= 3 datasets +* **Total regression dataset**: >= 7 datasets * **Total performance metrics (as fitness)**: > 30 metrics * **Documentation:** https://mafese.readthedocs.io/en/latest/ * **Python versions:** 3.7.x, 3.8.x, 3.9.x, 3.10.x, 3.11.x @@ -43,7 +43,7 @@ using meta-heuristic algorithms. Install the [current PyPI release](https://pypi.python.org/pypi/mafese): ```sh -$ pip install mafese==0.1.4 +$ pip install mafese==0.1.5 ``` ### Install directly from source code @@ -216,8 +216,7 @@ Or, use Metaheuristic-based feature selection with different metaheuristic algor ```python from mafese.wrapper.mha import MhaSelector -from mafese import get_dataset -from mafese import evaluator +from mafese import get_dataset, evaluator from sklearn.svm import SVC data = get_dataset("Arrhythmia") @@ -253,8 +252,7 @@ Or, use Lasso-based feature selection with different estimator: ```python from mafese.embedded.lasso import LassoSelector -from mafese import get_dataset -from mafese import evaluator +from mafese import get_dataset, evaluator from sklearn.svm import SVC @@ -289,8 +287,7 @@ Or, use Tree-based feature selection with different estimator: ```python from mafese.embedded.tree import TreeSelector -from mafese import get_dataset -from mafese import evaluator +from mafese import get_dataset, evaluator from sklearn.svm import SVC @@ -328,7 +325,7 @@ For more usage examples please look at [examples](/examples) folder. To call the class ```code -from mafese import Data, get_dataset +from mafese import Data, get_dataset, evaluator from mafese import FilterSelector from mafese import SequentialSelector, RecursiveSelector, MhaSelector from mafese import LassoSelector, TreeSelector @@ -383,5 +380,8 @@ If you are using mafese in your project, we would appreciate citations: 3. https://github.com/LBBSoft/FeatureSelect 4. https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-019-2754-0 5. https://github.com/scikit-learn-contrib/boruta_py -``` +6. https://elki-project.github.io/ +7. https://sci2s.ugr.es/keel/index.php +8. https://archive.ics.uci.edu/datasets +``` diff --git a/docs/source/index.rst b/docs/source/index.rst index b931e71..9ff9f4e 100644 --- a/docs/source/index.rst +++ b/docs/source/index.rst @@ -6,7 +6,7 @@ Welcome to MAFESE's documentation! ================================== -.. image:: https://img.shields.io/badge/release-0.1.4-yellow.svg +.. image:: https://img.shields.io/badge/release-0.1.5-yellow.svg :target: https://github.com/thieu1995/mafese/releases .. image:: https://img.shields.io/pypi/wheel/gensim.svg @@ -61,7 +61,7 @@ using meta-heuristic algorithms. * **Total Embedded-based (Tree and Lasso)**: > 10 methods * **Total Unsupervised-based**: >= 4 methods * **Total classification dataset**: >= 30 datasets -* **Total regression dataset**: >= 3 datasets +* **Total regression dataset**: >= 7 datasets * **Total performance metrics (as fitness)**: > 30 metrics * **Documentation:** https://mafese.readthedocs.io/en/latest/ * **Python versions:** 3.7.x, 3.8.x, 3.9.x, 3.10.x, 3.11.x diff --git a/docs/source/pages/quick_start.rst b/docs/source/pages/quick_start.rst index 4c2c171..f084492 100644 --- a/docs/source/pages/quick_start.rst +++ b/docs/source/pages/quick_start.rst @@ -4,7 +4,7 @@ Installation * Install the `current PyPI release `_:: - $ pip install mafese==0.1.4 + $ pip install mafese==0.1.5 * Install directly from source code:: diff --git a/mafese/__init__.py b/mafese/__init__.py index 49fa012..465785b 100644 --- a/mafese/__init__.py +++ b/mafese/__init__.py @@ -4,7 +4,7 @@ # Github: https://github.com/thieu1995 % # --------------------------------------------------% -__version__ = "0.1.4" +__version__ = "0.1.5" from mafese.utils.data_loader import Data, get_dataset from mafese.filter import FilterSelector diff --git a/run_fs.py b/run_fs.py index 802e0f2..9dc3a65 100644 --- a/run_fs.py +++ b/run_fs.py @@ -5,8 +5,7 @@ # --------------------------------------------------% from mafese.wrapper.mha import MhaSelector -from mafese import get_dataset -from mafese import evaluator +from mafese import get_dataset, evaluator from sklearn.svm import SVC diff --git a/setup.py b/setup.py index 80a690f..31a9283 100644 --- a/setup.py +++ b/setup.py @@ -15,7 +15,7 @@ def readme(): setup( name="mafese", - version="0.1.4", + version="0.1.5", author="Thieu", author_email="nguyenthieu2102@gmail.com", description="MAFESE: Metaheuristic Algorithm for Feature Selection - An Open Source Python Library",