lib/svmkit/linear_model/logistic_regression.rb in svmkit-0.2.5 vs lib/svmkit/linear_model/logistic_regression.rb in svmkit-0.2.6

- old
+ new

@@ -1,5 +1,7 @@ +# frozen_string_literal: true + require 'svmkit/base/base_estimator' require 'svmkit/base/classifier' module SVMKit # This module consists of the classes that implement generalized linear models. @@ -131,20 +133,9 @@ n_samples, = x.shape proba = Numo::DFloat.zeros(n_samples, 2) proba[true, 1] = sigmoid(decision_function(x)) proba[true, 0] = 1.0 - proba[true, 1] proba - end - - # Claculate the mean accuracy of the given testing data. - # - # @param x [Numo::DFloat] (shape: [n_samples, n_features]) Testing data. - # @param y [Numo::Int32] (shape: [n_samples]) True labels for testing data. - # @return [Float] Mean accuracy - def score(x, y) - p = predict(x) - n_hits = (y.to_a.map.with_index { |l, n| l == p[n] ? 1 : 0 }).inject(:+) - n_hits / y.size.to_f end # Dump marshal data. # @return [Hash] The marshal data about LogisticRegression. def marshal_dump