Example #1
0
	def adjust_coef(self, w):
		coef, intercept = baseRegression.adjust_coef(self, w)
		if self.penalty_ == "l1":
			# ===FIXME===
			# I don't know the condition to shrink the coef to 0
			coef = np.array([0.0 if abs(wi) < 1.0 else wi for wi in coef])
		return coef, intercept
Example #2
0
	def adjust_coef(self, w):
		if self.prob_func_ == "sigmoid":
			coef, intercept = baseRegression.adjust_coef(self, w)
		else: # self.prob_func_ == "softmax"
			coef = np.divide(w[:-1].T, self.scaler_.scale_)
			intercept = w[-1] - np.sum(coef * self.scaler_.mean_)
		if self.penalty_ == "l1":
			# ===FIXME===
			# I don't now the condition to shrink the coef to 0
			coef = np.array([0.0 if abs(wi) < 0.1 else wi for wi in coef])
			intercept = 0.0 if abs(intercept) < 0.1 else intercept
		return coef, intercept