spec/usage_spec.rb in rb-libsvm-1.0.5 vs spec/usage_spec.rb in rb-libsvm-1.0.6

- old
+ new

@@ -1,47 +1,47 @@ require 'spec_helper' describe "Basic usage" do - before do - @problem = Problem.new - @parameter = SvmParameter.new - @parameter.cache_size = 1 # mb + before do + @problem = Problem.new + @parameter = SvmParameter.new + @parameter.cache_size = 1 # mb - # "eps is the stopping criterion (we usually use 0.00001 in nu-SVC, - # 0.001 in others)." (from README) - @parameter.eps = 0.001 + # "eps is the stopping criterion (we usually use 0.00001 in nu-SVC, + # 0.001 in others)." (from README) + @parameter.eps = 0.001 - @parameter.c = 10 - end + @parameter.c = 10 + end - it "has a nice API" do - example = {11 => 0.11, 21 => 0.21, 101 => 0.99 }.to_example - example.should == Node.features({11 => 0.11, 21 => 0.21, 101 => 0.99 }) - end + it "has a nice API" do + example = {11 => 0.11, 21 => 0.21, 101 => 0.99 }.to_example + example.should == Node.features({11 => 0.11, 21 => 0.21, 101 => 0.99 }) + end - it "is as in [PCI,217]" do - examples = [ [1,0,1], [-1,0,-1] ].map {|ary| Node.features(ary) } - labels = [1, -1] - @problem.set_examples(labels, examples) + it "is as in [PCI,217]" do + examples = [ [1,0,1], [-1,0,-1] ].map {|ary| Node.features(ary) } + labels = [1, -1] + @problem.set_examples(labels, examples) - model = Model.train(@problem, @parameter) + model = Model.train(@problem, @parameter) - pred = model.predict(Node.features(1, 1, 1)) - pred.should == 1.0 + pred = model.predict(Node.features(1, 1, 1)) + pred.should == 1.0 - pred = model.predict(Node.features(-1, 1, -1)) - pred.should == -1.0 + pred = model.predict(Node.features(-1, 1, -1)) + pred.should == -1.0 - pred = model.predict(Node.features(-1, 55, -1)) - pred.should == -1.0 - end + pred = model.predict(Node.features(-1, 55, -1)) + pred.should == -1.0 + end - it "kernel parameter use" do - @parameter.kernel_type = SvmParameter::KernelType::RBF - examples = [[1, 2, 3], [-2, -2, -2]].map {|ary| Node.features(ary) } - @problem.set_examples([1, 2], examples) + it "kernel parameter use" do + @parameter.kernel_type = SvmParameter::KernelType::RBF + examples = [[1, 2, 3], [-2, -2, -2]].map {|ary| Node.features(ary) } + @problem.set_examples([1, 2], examples) - model = Model.train(@problem, @parameter) + model = Model.train(@problem, @parameter) - model.predict(Node.features(1, 2, 3)).should == 2 - end + model.predict(Node.features(1, 2, 3)).should == 2 + end end