cv-compare 0.1.0

Tool to quickly compare the performance of a set of baseline ML methodologies.

cv_compare

Tool to quickly compare the performance of a set of baseline ML methodologies using cross-validation.

• GitHub | PyPI
• Created by Harry Hesketh-Prichard | GitHub @hprich80 | PyPI @hprich80
• MIT License

Installation

pip install cv_compare

Usage

from cv_compare import cv_compare
from sklearn.datasets import make_classification

X, y = make_classification(n_samples=500, random_state=1)

results = cv_compare(X, y, task='classification')

results.summary_table   # ranked table of mean scores
results.plot()          # boxplot of CV score distributions

Arguments

Argument	Type	Default	Description
X	array-like	required	Feature matrix
y	array-like	required	Target vector
model_task	str	'classification'	'classification' or 'regression'
models	list	None	Replace default models with a custom list
add_models	list	None	Append models to the default list
random_state	int	1	Random seed
scaler	bool	True	Apply StandardScaler to each pipeline
cv_scoring	str	None	Sklearn scoring metric. Defaults to 'accuracy' for classification and 'neg_root_mean_squared_error' for regression

Models included

Classification: KNN, Logistic Regression, Decision Tree, Random Forest, Bagging (DT), Bagging (RF), AdaBoost, Gradient Boosting, Voting Classifier

Regression: Linear Regression, Decision Tree, Random Forest, Bagging (DT), Bagging (RF), AdaBoost, Gradient Boosting, Voting Regressor

Development

git clone [e-mail]:hprich80/cv_compare.git
cd cv_compare
pip install -e .

Run tests:

pytest

Author

cv_compare was created in 2026 by Harry Hesketh-Prichard.

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