Class: Svm::Problem

Inherits:
Object
  • Object
show all
Includes:
CrossValidation
Defined in:
lib/svm/problem.rb

Instance Attribute Summary collapse

Class Method Summary collapse

Instance Method Summary collapse

Methods included from CrossValidation

#cross_validate, #find_best_parameters, #results_for_cross_validation

Constructor Details

#initialize(user_options = {}) ⇒ Problem

Returns a new instance of Problem.



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# File 'lib/svm/problem.rb', line 24

def initialize(user_options = {})
  @nodes_pointers = []
  @options = Options.new(user_options)
end

Instance Attribute Details

#num_features ⇒ Object (readonly)

Returns the value of attribute num_features.



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# File 'lib/svm/problem.rb', line 8

def num_features
  @num_features
end

#num_samples ⇒ Object (readonly)

Returns the value of attribute num_samples.



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# File 'lib/svm/problem.rb', line 7

def num_samples
  @num_samples
end

#options ⇒ Object (readonly)

Returns the value of attribute options.



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# File 'lib/svm/problem.rb', line 9

def options
  @options
end

#scaler ⇒ Object

Returns the value of attribute scaler.



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# File 'lib/svm/problem.rb', line 11

def scaler
  @scaler
end

Class Method Details

.load_from_csv(csv_path, options = {}) ⇒ Object 



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# File 'lib/svm/problem.rb', line 13

def self.load_from_csv(csv_path, options = {})
  data = CSV.read(csv_path).collect do |row|
    row.collect { |field| field.to_f }
  end

  instance = self.new(options)
  instance.data = data

  instance
end

Instance Method Details

#data=(samples, weights = nil) ⇒ Object 



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# File 'lib/svm/problem.rb', line 29

def data=(samples, weights = nil)
  @num_samples    = samples.size
  @num_features   = samples.first.size - 1
  @sample_weights = weights if weights

  if options[:scale]
    self.scaler = Scaler.scale(samples)
    scaler.release_data!
  end

  problem_struct[:l] = num_samples
  problem_struct[:svm_node] = FFI::MemoryPointer.new(FFI::Pointer, num_samples)
  problem_struct[:y] = FFI::MemoryPointer.new(FFI::Type::DOUBLE, num_samples)
  problem_struct[:W] = FFI::MemoryPointer.new(FFI::Type::DOUBLE, num_samples)

  # Allocate memory for the samples
  # There are num_samples each with num_features nodes

  num_samples.times.each do |i|
    sample = samples[i].collect(&:to_f)

    sample_value  = sample.first
    sample_xs     = sample[1..sample.size-1]
    sample_weight = sample_weights[i]

    problem_struct[:y].put_double(FFI::Type::DOUBLE.size * i, sample_value)
    problem_struct[:W].put_double(FFI::Type::DOUBLE.size * i, sample_weight)

    # Allocate memory for the sample
    nodes_ptr = NodeStruct.node_array_from(sample_xs)
    problem_struct[:svm_node].put_pointer(FFI::Pointer.size*i, nodes_ptr)

    # We have to keep a reference to the pointer so it is not gargabe collected
    @nodes_pointers << nodes_ptr
  end
end

#estimate_probabilities=(option) ⇒ Object 



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# File 'lib/svm/problem.rb', line 128

def estimate_probabilities=(option)
  value = option ? 1 : 0

  options.parameter_struct[:probability] = value
end

#generate_model(more_options = {}) ⇒ Object 



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# File 'lib/svm/problem.rb', line 83

def generate_model(more_options = {})
  set(more_options)

  model_pointer = Svm.svm_train(problem_struct.pointer, options.parameter_struct.pointer)
  model_struct = ModelStruct.new(model_pointer)

  model = Model.new(model_struct)
  model.scaler = scaler

  model
end

#label_weights=(weights) ⇒ Object 



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# File 'lib/svm/problem.rb', line 111

def label_weights=(weights)
  options.label_weights = weights
  check_parameters!
end

#labels ⇒ Object 



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# File 'lib/svm/problem.rb', line 107

def labels
  num_samples.times.collect { |i| value(i) }.uniq
end

#length ⇒ Object 



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# File 'lib/svm/problem.rb', line 79

def length
  problem_struct[:l]
end

#num_samples_for(label) ⇒ Object 



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# File 'lib/svm/problem.rb', line 103

def num_samples_for(label)
  num_samples.times.count { |i| value(i) == label }
end

#sample(index) ⇒ Object 



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# File 'lib/svm/problem.rb', line 66

def sample(index)
  sample_ptr = @nodes_pointers[index]

  num_features.times.collect do |j|
    node = NodeStruct.new(sample_ptr + NodeStruct.size * j)
    node[:value]
  end
end

#sample_weights ⇒ Object 



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# File 'lib/svm/problem.rb', line 124

def sample_weights
  @sample_weights ||= Array.new(num_samples, 1.0)
end

#sample_weights=(weights) ⇒ Object 



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# File 'lib/svm/problem.rb', line 120

def sample_weights=(weights)
  @sample_weights = weights
end

#set(custom_options) ⇒ Object 



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# File 'lib/svm/problem.rb', line 134

def set(custom_options)
  options.add(custom_options)
  check_parameters!
end

#suggested_labels_weights ⇒ Object 



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# File 'lib/svm/problem.rb', line 95

def suggested_labels_weights
  labels.inject({}) do |hash, label|
    num = num_samples_for(label).to_f
    hash[label.to_i] = num/num_samples
    hash
  end
end

#value(index) ⇒ Object 



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# File 'lib/svm/problem.rb', line 75

def value(index)
  problem_struct[:y].get_double(FFI::Type::DOUBLE.size * index)
end

#weight_for(i) ⇒ Object 



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# File 'lib/svm/problem.rb', line 116

def weight_for(i)
  sample_weights[i] || 1.0
end