Ejemplos de LinearRidgeRegression.apply en Python

Ejemplo n.º 1

Archivo: regression_linear_ridge_modular.py Proyecto: harshitsyal/shogun

def regression_linear_ridge_modular (fm_train=traindat,fm_test=testdat,label_train=label_traindat,tau=1e-6):

	from shogun.Features import Labels, RealFeatures
	from shogun.Regression import LinearRidgeRegression

	rr=LinearRidgeRegression(tau, RealFeatures(traindat), Labels(label_train))
	rr.train()
	out = rr.apply(RealFeatures(fm_test)).get_labels()
	return out,rr

Ejemplo n.º 2

Archivo: regression_linear_ridge_modular.py Proyecto: vinodrajendran001/ASP

def regression_linear_ridge_modular(fm_train=traindat,
                                    fm_test=testdat,
                                    label_train=label_traindat,
                                    tau=1e-6):

    from shogun.Features import RegressionLabels, RealFeatures
    from shogun.Regression import LinearRidgeRegression

    rr = LinearRidgeRegression(tau, RealFeatures(traindat),
                               RegressionLabels(label_train))
    rr.train()
    out = rr.apply(RealFeatures(fm_test)).get_labels()
    return out, rr

Ejemplo n.º 3

Archivo: regression_lars.py Proyecto: serialhex/shogun

    lsr = LeastSquaresRegression()
    lsr.set_labels(Labels(y))
    lsr.train(RealFeatures(X.T))

# gather LASSO path
path = np.zeros((p, LeastAngleRegression.get_path_size()))
for i in xrange(path.shape[1]):
    path[:,i] = LeastAngleRegression.get_w(i)

# apply on training data
mse_train = np.zeros(LeastAngleRegression.get_path_size())
for i in xrange(mse_train.shape[0]):
    LeastAngleRegression.switch_w(i)
    ypred = LeastAngleRegression.apply(RealFeatures(X.T)).get_labels()
    mse_train[i] = np.dot(ypred - y, ypred - y) / y.shape[0]
ypred = lsr.apply(RealFeatures(X.T)).get_labels()
mse_train_lsr = np.dot(ypred - y, ypred - y) / y.shape[0]

# apply on test data
mse_test = np.zeros(LeastAngleRegression.get_path_size())
for i in xrange(mse_test.shape[0]):
    LeastAngleRegression.switch_w(i)
    ypred = LeastAngleRegression.apply(RealFeatures(Xtest.T)).get_labels()
    mse_test[i] = np.dot(ypred - ytest, ypred - ytest) / ytest.shape[0]
ypred = lsr.apply(RealFeatures(Xtest.T)).get_labels()
mse_test_lsr = np.dot(ypred - ytest, ypred - ytest) / ytest.shape[0]

fig = plt.figure()
ax_path = fig.add_subplot(1,2,1)
plt.plot(xrange(path.shape[1]), path.T, '.-')
plt.legend(['%d' % (x+1) for x in xrange(path.shape[0])])

Ejemplo n.º 4

Archivo: regression_lars.py Proyecto: vinodrajendran001/ASP

    lsr = LeastSquaresRegression()
    lsr.set_labels(RegressionLabels(y))
    lsr.train(RealFeatures(X.T))

# gather LASSO path
path = np.zeros((p, LeastAngleRegression.get_path_size()))
for i in xrange(path.shape[1]):
    path[:, i] = LeastAngleRegression.get_w(i)

# apply on training data
mse_train = np.zeros(LeastAngleRegression.get_path_size())
for i in xrange(mse_train.shape[0]):
    LeastAngleRegression.switch_w(i)
    ypred = LeastAngleRegression.apply(RealFeatures(X.T)).get_labels()
    mse_train[i] = np.dot(ypred - y, ypred - y) / y.shape[0]
ypred = lsr.apply(RealFeatures(X.T)).get_labels()
mse_train_lsr = np.dot(ypred - y, ypred - y) / y.shape[0]

# apply on test data
mse_test = np.zeros(LeastAngleRegression.get_path_size())
for i in xrange(mse_test.shape[0]):
    LeastAngleRegression.switch_w(i)
    ypred = LeastAngleRegression.apply(RealFeatures(Xtest.T)).get_labels()
    mse_test[i] = np.dot(ypred - ytest, ypred - ytest) / ytest.shape[0]
ypred = lsr.apply(RealFeatures(Xtest.T)).get_labels()
mse_test_lsr = np.dot(ypred - ytest, ypred - ytest) / ytest.shape[0]

fig = plt.figure()
ax_path = fig.add_subplot(1, 2, 1)
plt.plot(xrange(path.shape[1]), path.T, '.-')
plt.legend(['%d' % (x + 1) for x in xrange(path.shape[0])])

Ejemplo n.º 5

    lsr.train(RealFeatures(X.T))

# gather LASSO path
path = np.zeros((p, LeastAngleRegression.get_path_size()))
for i in xrange(path.shape[1]):
    path[:, i] = LeastAngleRegression.get_w(i)

evaluator = MeanSquaredError()

# apply on training data
mse_train = np.zeros(LeastAngleRegression.get_path_size())
for i in xrange(mse_train.shape[0]):
    LeastAngleRegression.switch_w(i)
    ypred = LeastAngleRegression.apply(RealFeatures(X.T))
    mse_train[i] = evaluator.evaluate(ypred, RegressionLabels(y))
ypred = lsr.apply(RealFeatures(X.T))
mse_train_lsr = evaluator.evaluate(ypred, RegressionLabels(y))

# apply on test data
mse_test = np.zeros(LeastAngleRegression.get_path_size())
for i in xrange(mse_test.shape[0]):
    LeastAngleRegression.switch_w(i)
    ypred = LeastAngleRegression.apply(RealFeatures(Xtest.T))
    mse_test[i] = evaluator.evaluate(ypred, RegressionLabels(y))
ypred = lsr.apply(RealFeatures(Xtest.T))
mse_test_lsr = evaluator.evaluate(ypred, RegressionLabels(y))

fig = plt.figure()
ax_path = fig.add_subplot(1, 2, 1)
plt.plot(xrange(path.shape[1]), path.T, '.-')
plt.legend(['%d' % (x + 1) for x in xrange(path.shape[0])])

Ejemplo n.º 6

Archivo: regression_lars.py Proyecto: AlexBinder/shogun

    lsr.train(RealFeatures(X.T))

# gather LASSO path
path = np.zeros((p, LeastAngleRegression.get_path_size()))
for i in xrange(path.shape[1]):
    path[:,i] = LeastAngleRegression.get_w(i)

evaluator = MeanSquaredError()

# apply on training data
mse_train = np.zeros(LeastAngleRegression.get_path_size())
for i in xrange(mse_train.shape[0]):
    LeastAngleRegression.switch_w(i)
    ypred = LeastAngleRegression.apply(RealFeatures(X.T))
    mse_train[i] = evaluator.evaluate(ypred, RegressionLabels(y))
ypred = lsr.apply(RealFeatures(X.T))
mse_train_lsr = evaluator.evaluate(ypred, RegressionLabels(y))

# apply on test data
mse_test = np.zeros(LeastAngleRegression.get_path_size())
for i in xrange(mse_test.shape[0]):
    LeastAngleRegression.switch_w(i)
    ypred = LeastAngleRegression.apply(RealFeatures(Xtest.T))
    mse_test[i] = evaluator.evaluate(ypred, RegressionLabels(y))
ypred = lsr.apply(RealFeatures(Xtest.T))
mse_test_lsr = evaluator.evaluate(ypred, RegressionLabels(y))

fig = plt.figure()
ax_path = fig.add_subplot(1,2,1)
plt.plot(xrange(path.shape[1]), path.T, '.-')
plt.legend(['%d' % (x+1) for x in xrange(path.shape[0])])