def train_rls():
#Trains RLS with automatically selected regularization parameter
X_train, Y_train, X_test, Y_test = load_housing()
regparams = [2.**i for i in range(-15, 16)]
learner = LeaveOneOutRLS(X_train, Y_train, regparams = regparams)
loo_errors = learner.cv_performances
P_test = learner.predict(X_test)
print("leave-one-out errors " +str(loo_errors))
print("chosen regparam %f" %learner.regparam)
print("test error %f" %sqerror(Y_test, P_test))
def train_rls():
#Trains RLS with automatically selected regularization parameter
X_train, Y_train, X_test, Y_test = load_housing()
regparams = [2.**i for i in range(-15, 16)]
learner = LeaveOneOutRLS(X_train, Y_train, regparams = regparams, measure=cindex)
loo_errors = learner.cv_performances
P_test = learner.predict(X_test)
print("leave-one-out cindex " +str(loo_errors))
print("chosen regparam %f" %learner.regparam)
print("test cindex %f" %cindex(Y_test, P_test))
def train_rls():
X_train, Y_train, X_test, Y_test = load_wine()
#Map labels from set {1,2,3} to one-vs-all encoding
Y_train = to_one_vs_all(Y_train, False)
Y_test = to_one_vs_all(Y_test, False)
regparams = [2.**i for i in range(-15, 16)]
learner = LeaveOneOutRLS(X_train, Y_train, regparams=regparams, measure=ova_accuracy)
P_test = learner.predict(X_test)
#ova_accuracy computes one-vs-all classification accuracy directly between transformed
#class label matrix, and a matrix of predictions, where each column corresponds to a class
print("test set accuracy %f" %ova_accuracy(Y_test, P_test))
def train_rls():
X_train, Y_train, X_test, Y_test = load_wine()
#Map labels from set {1,2,3} to one-vs-all encoding
Y_train = to_one_vs_all(Y_train)
Y_test = to_one_vs_all(Y_test)
regparams = [2.**i for i in range(-15, 16)]
learner = LeaveOneOutRLS(X_train, Y_train, regparams=regparams, measure=ova_accuracy)
P_test = learner.predict(X_test)
#ova_accuracy computes one-vs-all classification accuracy directly between transformed
#class label matrix, and a matrix of predictions, where each column corresponds to a class
print("test set accuracy %f" %ova_accuracy(Y_test, P_test))
