Class: Svm::Model

Inherits:
Object
  • Object
show all
Defined in:
lib/svm/model.rb

Instance Attribute Summary collapse

Class Method Summary collapse

Instance Method Summary collapse

Constructor Details

#initialize(model_struct) ⇒ Model

Returns a new instance of Model.



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

def initialize(model_struct)
  @model_struct = model_struct
end

Instance Attribute Details

#model_struct ⇒ Object (readonly)

Returns the value of attribute model_struct.



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# File 'lib/svm/model.rb', line 6

def model_struct
  @model_struct
end

#scaler ⇒ Object

Returns the value of attribute scaler.



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

def scaler
  @scaler
end

Class Method Details

.load(path) ⇒ Object

Raises:



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# File 'lib/svm/model.rb', line 18

def self.load(path)
  model_struct_pointer = Svm.svm_load_model(path)
  raise ModelSerializationError.new("Unable to load model from file. Error: #{result}") unless model_struct_pointer != FFI::Pointer::NULL
  
  model_struct = ModelStruct.new(model_struct_pointer)
  self.new(model_struct)
end

Instance Method Details

#labels ⇒ Object 



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# File 'lib/svm/model.rb', line 30

def labels
  labels_array = FFI::MemoryPointer.new(:int, number_of_classes)
  
  Svm.svm_get_labels(model_struct, labels_array)
  
  labels_array.read_array_of_int(number_of_classes)
end

#number_of_classes ⇒ Object 



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# File 'lib/svm/model.rb', line 26

def number_of_classes
  Svm.svm_get_nr_class(model_struct)
end

#predict(sample) ⇒ Object 



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# File 'lib/svm/model.rb', line 38

def predict(sample)
  scaler.scale(sample) if scaler
  
  nodes_ptr = NodeStruct.node_array_from(sample)
  Svm.svm_predict(model_struct, nodes_ptr)
end

#predict_probabilities(sample) ⇒ Object 



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# File 'lib/svm/model.rb', line 45

def predict_probabilities(sample)
  unless Svm.svm_check_probability_model(model_struct) == 1
    raise ModelError.new("Model doesn't have probability info")
  end
  
  scaler.scale(sample) if scaler
  
  nodes_ptr = NodeStruct.node_array_from(sample)
  
  prob_array = FFI::MemoryPointer.new(:double, number_of_classes)
  
  Svm.svm_predict_probability(model_struct, nodes_ptr, prob_array)
  probabilities = prob_array.read_array_of_double(number_of_classes)
  
  number_of_classes.times.inject({}) do |hash, index|
    label = labels[index]
    prob  = probabilities[index]
    
    hash[label] = prob
    hash
  end
end

#save(path) ⇒ Object

Raises:



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

def save(path)
  result = Svm.svm_save_model(path, model_struct.pointer)
  raise ModelSerializationError.new("Unable to save model to file. Error: #{result}") unless result == 0
end