Quickstart

A quick example how to evaluate the results of a trained model.

# Import library
import classeval

# Train model and derive probabilities
X, y = clf.load_example('breast')
X_train, X_test, y_train, y_true = train_test_split(X, y, test_size=0.2)
model = gb.fit(X_train, y_train)
y_proba = model.predict_proba(X_test)[:,1]
y_pred = model.predict(X_test)

# Evaluate the models performance
out = clf.eval(y_true, y_proba, pos_label='malignant')

# Plot results
ax = clf.plot(out)

Installation

Install via pip:

# Installation from pypi
pip install classeval

Install via github source:

# Install directly from github
pip install git+https://github.com/erdogant/classeval

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