Metadata-Version: 2.1
Name: hal-x
Version: 0.52
Summary: Clustering via hierarchical agglomerative learning
Home-page: https://alexandreday.github.io/
Author: Alexandre Day
Author-email: alexandre.day1@gmail.com
License: MIT
Description: # Hierarchical Agglomerative Learning (HAL)
        Package for performing clustering for high-dimensional data. This packages uses heavily scikit-learn and fft accelerated t-SNE. 
        
        # Installing (once)
        Activate an [Anaconda](https://conda.io/docs/user-guide/tasks/manage-environments.html) Python 3 environment
        ```
        conda config --add channels conda-forge
        conda install cython numpy fftw
        pip install hal-x
        ```
        # Updating
        Again from your Anaconda Python 3 environment:
        ```
        pip install hal-x --upgrade
        ```
        # Example of use
        ```
        from hal import HAL
        from sklearn.datasets import make_blobs
        
        # generate some data
        X,y = make_blobs(10000,12,10) # 10 blobs in 12 dimensions, 10000 data points
        
        model = HAL(clf_type='rf')
        
        # builds model and outputs intermediate plots/results
        model.fit(X)
        
        # predict new labels
        
        ypred = HAL.predict(X)
        ```
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
