import?numpy?as?np
import?pandas?as?pd
import?matplotlib.pyplot?as?plt
from?sklearn?import?linear_model
from?sklearn?import?preprocessing
from?sklearn.model_selection?import?train_test_split
import?copy

class?Algorithm:
	“““
	This?is?a?demo?of?using?coordinate?descent?algorithm?（including?both?cyclic?coordinate?descent?
	and?randomized?coordinate?descent）?to?solve?the?LASSO?problem?that?is?the?‘l1-regularized?
	least-squares?regression?problem.

	“““
	def?__init__（self?lambduh=6.46?max_iter=1000）:
		“““
		Coordinate?descent?algorithm?to?solve?the?LASSO?problem.

		Parameters
		----------
		lambduh?:?float
		Regularization?parameter.
		The?default?lambduh?is?set?as?6.46?（the?optimal?lambduh?from?cross?validation?result）.?
		However?users?are?allowed?set?lambduh?in?the?__main__?function