コード例 #1
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    def _importance(self, feature):
        prior_prediction = self.predict(
            [util.bias_feature()] +
            [pb.Feature()] * (self._config.num_features - 1))
        with_weight_prediction = self.predict(
            [util.bias_feature()] +
            [pb.Feature()] * (self._config.num_features - 2) + [feature])

        return util.kl_divergence(with_weight_prediction, prior_prediction)
コード例 #2
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    def _importance(self, feature):
        prior_prediction = self.predict([util.bias_feature()] +
                                        [pb.Feature()] *
                                        (self._config.num_features - 1))
        with_weight_prediction = self.predict([util.bias_feature()] +
                                              [pb.Feature()] *
                                              (self._config.num_features - 2) +
                                              [feature])

        return util.kl_divergence(with_weight_prediction, prior_prediction)
コード例 #3
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    def __init__(self, config):
        self._config = config
        self._weights = {}

        # Initial bias weight
        bias_weight = util.prior_bias_weight(config.prior_probability,
                                             config.beta, config.num_features)

        self._set_weight(util.bias_feature(), bias_weight)
コード例 #4
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    def __init__(self, config):
        self._config = config
        self._weights = {}

        # Initial bias weight
        bias_weight = util.prior_bias_weight(
            config.prior_probability,
            config.beta,
            config.num_features)

        self._set_weight(util.bias_feature(), bias_weight)
コード例 #5
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 def _create_feature_vector(num_features):
     return [util.bias_feature()] + \
         [pb.Feature()] * (num_features - 1)