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#include "multinomial_bayes_classifier.h" #include "data_set/data_set.h" #include <math.h> double Classifier::MultinomialBayesClassifier::score(DataSet::Category *category, DataSet::Example *example) { } void Classifier::MultinomialBayesClassifier::prepare() { numeric_feature_probabilities.resize(data_set->categories_size() + 1); nominal_feature_probabilities.resize(data_set->categories_size() + 1); DataSet::NumericFeature *numeric_feature = NULL; DataSet::NominalFeature *nominal_feature = NULL; int feature_count = data_set->features.size(); double category_sum = 0.0; data_set->count(); // determine the category probabilities for each feature for(int i = 1; i <= data_set->categories_size(); i++) { numeric_feature_probabilities[i].reserve(feature_count); nominal_feature_probabilities[i].reserve(feature_count); // sum the counts of each numeric feature for this category category_sum = 0.0 for(int j = 0; j < numeric_features.size(); j++) category_sum += numeric_features[j]->category_sum(i); category_sum += numeric_features.size(); // weight each numeric feature only by the number of other numeric features; nominal features are handled separately for(int j = 0; j < numeric_features.size(); j++) numeric_feature_probabilities[i][j] = (1.0 + numeric_features[j]->category_sum(i)) / (category_sum); // each value of a nominal feature is treated as if it were another feature in itself for(int j = 0; j < nominal_features.size(); j++) { nominal_feature = nominal_features[j]; nominal_feature_probabilities[j].resize(nominal_feature->values.size()); } } }
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8 entries across 8 versions & 1 rubygems