def __init__(self, table,reg=False,lamda=0):
"""Initializes Class for Linear Regression
Parameters
----------
table : ndarray(n-rows,m-features + 1)
Numerical training data, last column as training values
reg : Boolean
Set True to enable regularization, false by default
"""
#regularization parameters
self.reg = reg
self.lamda = lamda
self.num_training = np.shape(table)[0]
# remove the last column from training data to extract features data
self.X = np.delete(table, -1, 1)
# add a column of ones in front of the training data
self.X = np.insert(self.X, 0, np.ones(self.num_training), axis=1)
self.num_features = np.shape(self.X)[1]
# extract the values of the training set from the provided data
self.y = table[:, self.num_features - 1]
# create parameters and initialize to 1
self.theta = np.ones(self.num_features)
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