lib/eps/linear_regression.rb in eps-0.3.9 vs lib/eps/linear_regression.rb in eps-0.4.0

@@ -35,12 +35,11 @@
       str += "r2: %.3f\n" % [r2] if extended
       str += "adjusted r2: %.3f\n" % [adjusted_r2]
       str
     end
 
-    # TODO use keyword arguments for gsl and intercept in 0.4.0
-    def _train(**options)
+    def _train(intercept: true, gsl: nil)
       raise "Target must be numeric" if @target_type != "numeric"
       check_missing_value(@train_set)
       check_missing_value(@validation_set) if @validation_set
 
       data = prep_x(@train_set)
@@ -49,44 +48,28 @@
         raise "Number of data points must be at least two more than number of features"
       end
 
       x = data.map_rows(&:to_a)
 
-      gsl =
-        if options.key?(:gsl)
-          options[:gsl]
-        elsif defined?(GSL)
-          true
-        elsif defined?(GSLR)
-          :gslr
-        else
-          false
-        end
+      gsl = defined?(GSLR) if gsl.nil?
 
-      intercept = options.key?(:intercept) ? options[:intercept] : true
-      if intercept && gsl != :gslr
+      if intercept && !gsl
         data.size.times do |i|
           x[i].unshift(1)
         end
       end
 
       v3 =
-        if gsl == :gslr
+        if gsl
           model = GSLR::OLS.new(intercept: intercept)
           model.fit(x, data.label, weight: data.weight)
 
           @covariance = model.covariance
 
           coefficients = model.coefficients.dup
           coefficients.unshift(model.intercept) if intercept
           coefficients
-        elsif gsl
-          x = GSL::Matrix.alloc(*x)
-          y = GSL::Vector.alloc(data.label)
-          w = GSL::Vector.alloc(data.weight) if data.weight
-          c, @covariance, _, _ = w ? GSL::MultiFit.wlinear(x, w, y) : GSL::MultiFit.linear(x, y)
-          c.to_a
         else
           x = Matrix.rows(x)
           y = Matrix.column_vector(data.label)
 
           # weighted OLS
@@ -193,16 +176,10 @@
     end
 
     def p_value
       @p_value ||= begin
         Hash[@coefficients.map do |k, _|
-          tp =
-            if @gsl
-              GSL::Cdf.tdist_P(t_value[k].abs, degrees_of_freedom)
-            else
-              Eps::Statistics.tdist_p(t_value[k].abs, degrees_of_freedom)
-            end
-
+          tp = Eps::Statistics.tdist_p(t_value[k].abs, degrees_of_freedom)
           [k, 2 * (1 - tp)]
         end]
       end
     end