Metadata-Version: 1.1
Name: EVBUS
Version: 0.0.3
Summary: Estimate Variance Based on U-Statistics (EVBUS)
Home-page: https://github.com/liyao001/EVBUS
Author: Li Yao
Author-email: yaol17@mails.tsinghua.edu.cn
License: Apache 2.0
Description-Content-Type: UNKNOWN
Description: EVBUS: Estimate Variance Based on U-Statistics
        ==============================================
        
        This is a python implementation of the paper: Mentch, L. & Hooker, G. Quantifying Uncertainty in Random Forests via Confidence Intervals and Hypothesis Tests. *J. Mach. Learn. Res*. 17, 1–41 (2016).
        
        Installation
        ------------
        ::
        
            pip install EVBUS
            
        Usage
        -----
        ::
        
            from EVBUS import EVBUS
            from sklearn.datasets import load_boston
            import sklearn.model_selection as xval
        
            boston = load_boston()
            Y = boston.data[:, 12]
            X = boston.data[:, 0:12]
        
            bos_X_train, bos_X_test, bos_y_train, bos_y_test = xval.train_test_split(X, Y, test_size=0.3)
            evbus = EVBUS.varU(bos_X_train, bos_y_train, bos_X_test)
        
            v = evbus.calculate_variance()
            print(v)
        
Platform: UNKNOWN
Classifier: Intended Audience :: Science/Research
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Topic :: Scientific/Engineering
