Machine learning's parameter search and feature selection module which is integrated log management and visualization.
BSD-2-CLAUSE License
cvopt (cross validation optimizer) is python module for machine learning's parameter search and feature selection. To simplify modeling, in cvopt, log management and visualization are integrated and the API like scikit-learn is provided.
In Data Science modeling, sometimes would like to ...
To make these simpler, cvopt was created.
$ pip install Gpy
$ pip install cvopt
Requires:
param_distributions = {"penalty": search_category(['l1', 'l2']), "C": search_numeric(0, 3, "float"),
"tol" : search_numeric(0, 4, "float"), "class_weight" : search_category([None, "balanced"])}
feature_groups = np.random.randint(0, 5, Xtrain.shape[1])
opt = SimpleoptCV(estimator=LogisticRegression(), param_distributions=param_distributions)
opt.fit(Xtrain, ytrain, feature_groups=feature_groups)