Metadata-Version: 1.1
Name: cudatree
Version: 0.6
Summary: Random Forests for the GPU using PyCUDA
Home-page: https://github.com/EasonLiao/CudaTree
Author: Yisheng Liao and Alex Rubinsteyn
Author-email: ['yl1912@nyu.edu / alexr@cs.nyu.edu']
License: BSD
Description: 
        CudaTree
        ========
        
        CudaTree is an implementation of Leo Breiman's Random Forests adapted to run on the GPU. A random forest is an ensemble of randomized decision trees which vote together to predict new labels. CudaTree parallelizes the construction of each individual tree in the ensemble and thus is able to train faster than the latest version of scikits-learn.
        
        Usage
        -------------
        
        ::
        
          import numpy as np
          from cudatree import load_data, RandomForestClassifier
          x_train, y_train = load_data("digits")
          forest = RandomForestClassifier(n_estimators = 50, max_features = 6)
          forest.fit(x_train, y_train)
          forest.predict(x_train)
        
        Dependencies
        --------------
        
        CudaTree is writen for Python 2.7 and depends on:
        
        * scikit-learn
        * NumPy
        * PyCUDA
        *  Parakeet
        
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Scientific/Engineering
Classifier: License :: OSI Approved :: BSD License
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python :: 2.7
