def train_lr():
train_x, train_y = regression.load_data_set('abalone.txt')
# calculate the training y using the data set of the 0-100 samples
y_train_hat1 = regression.local_weight_array_test(train_x[0:99], train_x[0:99], train_y[0:99], k=0.1)
y_train_hat2 = regression.local_weight_array_test(train_x[0:99], train_x[0:99], train_y[0:99], k=1)
y_train_hat3 = regression.local_weight_array_test(train_x[0:99], train_x[0:99], train_y[0:99], k=10)
# calculate the training error and print
y_train_error1 = res_error(train_y[0:99], y_train_hat1.T)
y_train_error2 = res_error(train_y[0:99], y_train_hat2.T)
y_train_error3 = res_error(train_y[0:99], y_train_hat3.T)
print 'k = 0.1, training error is: ', y_train_error1
print 'k = 1, training error is: ', y_train_error2
print 'k = 10, training error is: ', y_train_error3
print '=' * 50
# calculate the test y using the data set of the 100-199 samples
y_test_hat1 = regression.local_weight_array_test(train_x[100:199], train_x[0:99], train_y[0:99], k=0.1)
y_test_hat2 = regression.local_weight_array_test(train_x[100:199], train_x[0:99], train_y[0:99], k=1)
y_test_hat3 = regression.local_weight_array_test(train_x[100:199], train_x[0:99], train_y[0:99], k=10)
# calculate the test error and print
y_test_error1 = res_error(train_y[100:199], y_test_hat1.T)
y_test_error2 = res_error(train_y[100:199], y_test_hat2.T)
y_test_error3 = res_error(train_y[100:199], y_test_hat3.T)
print 'k = 0.1, test error is: ', y_test_error1
print 'k = 1, test error is: ', y_test_error2
print 'k = 10, test error is: ', y_test_error3
def ridge_test():
import matplotlib.pyplot as plt
x_mat, y_mat = regression.load_data_set('abalone.txt')
ridge_weights = ridge_train(x_mat, y_mat)
fig = plt.figure()
ax = fig.add_subplot(111)
ax.plot(ridge_weights)
plt.show()
def ridge_test():
import matplotlib.pyplot as plt
x_mat, y_mat = regression.load_data_set('abalone.txt')
ridge_weights = ridge_train(x_mat, y_mat)
fig = plt.figure()
ax = fig.add_subplot(111)
ax.plot(ridge_weights)
plt.show()
def test_plot_weight():
x_arr, y_arr = regression.load_data_set('ex0.txt')
regression.plot_local_weight([1.0, 0.5], x_arr, k=0.1)
def test_basic():
x_arr, y_arr = regression.load_data_set('ex0.txt')
w = regression.calc_weight(x_arr, y_arr)
print w
def test_stage():
x_arr, y_arr = regression.load_data_set('abalone.txt')
stage_wise(x_arr, y_arr, 0.01, 200)
def test_plot_weight():
x_arr, y_arr = regression.load_data_set('ex0.txt')
regression.plot_local_weight([1.0, 0.5], x_arr, k=0.1)
def test_basic():
x_arr, y_arr = regression.load_data_set('ex0.txt')
w = regression.calc_weight(x_arr, y_arr)
print w