c2333cd3917685075a239ff32a41594e21b2268e,recordlinkage/classifiers.py,BernoulliEMClassifier,learn,#BernoulliEMClassifier#Any#Any#Any#,507

Before Change

		
		// Default parameters
		if not params_init:
			params_init = {
				"p": 0.05,
				"m": {feature: {0: 0.1, 1:0.9} for feature in list(comparison_vectors)},
				"u": {feature: {0: 0.9, 1:0.1} for feature in list(comparison_vectors)}
			}
		
		self.classifier.p_init = params_init

		// Start training the classifier

After Change

		probs = self.algorithm.train(comparison_vectors.as_matrix())

		n_matches = int(self.algorithm.p*len(probs))
		self.p_threshold = numpy.sort(probs)[len(probs)-n_matches]

		prediction = self._decision_rule(probs, self.p_threshold)

Instances