A classifier that endeavors to solve the saddle point problem for AUC maximization.
Project description
CalfMilp
CalfMilp is a binomial classifier that implements a course approximation linear function by mixed integer linear programming.
Contact
Rolf Carlson hrolfrc@gmail.com
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_splitMake 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
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