Quick Start

from calfcv import CalfCV
from sklearn.datasets import make_classification
from sklearn.model_selection import train_test_split

Make a classification problem

seed = 42
X, y = make_classification(
    n_samples=30,
    n_features=5,
    n_informative=2,
    n_redundant=2,
    n_classes=2,
    random_state=seed
)
X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=seed)

Train the classifier

cls = CalfCV().fit(X_train, y_train)

Get the score on unseen data

cls.score(X_test, y_test)

0.875