Estimate Variance Based on U-Statistics (EVBUS)
Project description
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)
Project details
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