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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def set_params(self, **params):
 		""" Set the parameters of the estimator. 		Args: 			bias (array-like) : bias of the estimator. Also known as the intercept in a linear model. 			weights (array-like) : weights of the features. Also known as coeficients. 			NER biases (array-like) : NER entities infering column position on X and bias value. Ex: `b_4=10, b_5=6`. 		Example: 		"""

		if 'bias' in params.keys():
			self.intercept_ = params['bias']
		if 'weights' in params.keys():
			self.coef_ = params['weights']
		for key in params.keys():
			if 'b_' == key[:2]:
				self.B[int(key[2:])] = params[key]

		return self