calf-milp 0.1.8

A classifier that endeavors to solve the saddle point problem for AUC maximization.

CalfMilp

CalfMilp is a binomial classifier that implements a course approximation linear function by mixed integer linear programming.

Contact

Rolf Carlson [e-mail]

Install

Use pip to install calf-milp.

pip install calf-milp

Introduction

CalfMilp provides classification and prediction for two classes, the binomial case. Small problems are supported. This is research code and a work in progress.

CalfMilp is designed for use with scikit-learn pipelines and composite estimators.

Example

from calf_milp import CalfMilp
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 = CalfMilp().fit(X_train, y_train)

Get the score on unseen data

cls.score(X_test, y_test)

0.875