Metadata-Version: 1.1
Name: EVBUS
Version: 0.0.2
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: 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: License :: OSI Approved :: Apache
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Topic :: Scientific/Engineering
