@@ -0,0 +1,822 @@
+from __future__ import division, print_function, with_statement%0A%0Afrom sklearn import svm%0Afrom sklearn import datasets%0Afrom sklearn import cross_validation%0A%0Afrom orges.core import param%0Afrom orges.core.main import optimize%0Afrom orges.optimizer.saes import SAESOptimizer%0Afrom orges.plugins.print import PrintPlugin%0A%0A%0A@param.float(%22C%22, interval=%5B0.1, 100%5D)%0A@param.float(%22gamma%22, interval=%5B0, 100%5D)%0Adef f(C, gamma):%0A    iris = datasets.load_iris()%0A%0A    X_train, X_test, y_train, y_test = cross_validation.train_test_split(%0A        iris.data, iris.target, test_size=0.4, random_state=0)%0A%0A    clf = svm.SVC(C=C, gamma=gamma)%0A%0A    clf.fit(X_train, y_train)%0A%0A    return -clf.score(X_test, y_test)%0A%0A%0Aif __name__ == '__main__':%0A    print(optimize(f, timeout=5, optimizer=SAESOptimizer(),%0A                   plugins=%5BPrintPlugin()%5D))

Add SVM classification example