def test_process(self):
iris_mat_train, iris_label_train = dataset.load_iris("sample_data", "training", one_hot=True)
iris_mat_test, iris_label_test = dataset.load_iris("sample_data", "testing", one_hot=True)
linear_reg = LinearRegression(iris_mat_train, iris_label_train)
linear_reg.fit(lr = 0.0001, epoch = 1000, batch_size = 20)
error_rate = autotest.eval_predict(linear_reg, iris_mat_test, iris_label_test, self.logging, one_hot=True)
self.tlog("iris predict (with linear regression) error rate :" + str(error_rate))
def test_process(self):
train_mat = [\
[0.12, 0.25],\
[3.24, 4.33],\
[0.14, 0.45],\
[7.30, 4.23],\
]
train_label = [[0,1],[1,0],[0,1],[1,0]]
linear_reg =\
LinearRegression(train_mat, train_label)
linear_reg.fit(lr = 0.001, epoch = 1000, batch_size = 4)
r1 = autotest.eval_predict_one(linear_reg,[0.10,0.33],[0, 1],self.logging, one_hot = True)
r2 = autotest.eval_predict_one(linear_reg,[4.40,4.37],[1, 0],self.logging, one_hot = True)
