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