Metadata-Version: 1.1
Name: visualml
Version: 0.1b4
Summary: VisualML: Visualization of Multi-Dimensional Machine Learning Models
Home-page: https://github.com/wittmannf/visual-ml/
Author: Fernando Marcos Wittmann
Author-email: fernando.wittmann@gmail.com
License: BSD-4-Clause
Description: Visual ML is a library for visualizing the decision boundary of 
        machine learning models from Sklearn using 2D projections of pairs
        of features. Here's an example:
        ```
        >>> import visualml as vml
        >>> import pandas as pd
        >>> from sklearn.datasets import make_classification
        >>> from sklearn.ensemble import RandomForestClassifier as RF
         
        >>> # Create a toy classification dataset
        >>> feature_names = ['A','B','C','D']
        >>> X, y = make_classification(n_features=4, random_state=42)
         
        >>> # The visualization is only supported if X is a pandas df
        >>> X = pd.DataFrame(X, columns=feature_names)
         
        >>> # Train a classifier
        >>> clf = RF(random_state=42).fit(X,y) 
         
        >>> # Plot decision boundary grid
        >>> vml.decision_boundary_grid(clf, X, y)
        ```
        
        
Keywords: visualml
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: BSD License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
