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)