Class: OCI::AiLanguage::Models::EntityMetrics

Inherits:
Object
  • Object
show all
Defined in:
lib/oci/ai_language/models/entity_metrics.rb

Overview

Entity level named entity recognition model metrics

Instance Attribute Summary collapse

Class Method Summary collapse

Instance Method Summary collapse

Constructor Details

#initialize(attributes = {}) ⇒ EntityMetrics

Initializes the object

Parameters:

  • attributes (Hash) (defaults to: {}) —

    Model attributes in the form of hash

Options Hash (attributes):

  • :label (String) —

    The value to assign to the #label property

  • :f1 (Float) —

    The value to assign to the #f1 property

  • :precision (Float) —

    The value to assign to the #precision property

  • :recall (Float) —

    The value to assign to the #recall property



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# File 'lib/oci/ai_language/models/entity_metrics.rb', line 61

def initialize(attributes = {})
  return unless attributes.is_a?(Hash)

  # convert string to symbol for hash key
  attributes = attributes.each_with_object({}) { |(k, v), h| h[k.to_sym] = v }

  self.label = attributes[:'label'] if attributes[:'label']

  self.f1 = attributes[:'f1'] if attributes[:'f1']

  self.precision = attributes[:'precision'] if attributes[:'precision']

  self.recall = attributes[:'recall'] if attributes[:'recall']
end

Instance Attribute Details

#f1 ⇒ Float

[Required] F1-score, is a measure of a modelu2019s accuracy on a dataset

Returns:

  • (Float) 


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# File 'lib/oci/ai_language/models/entity_metrics.rb', line 17

def f1
  @f1
end

#label ⇒ String

[Required] Entity label

Returns:

  • (String) 


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# File 'lib/oci/ai_language/models/entity_metrics.rb', line 13

def label
  @label
end

#precision ⇒ Float

[Required] Precision refers to the number of true positives divided by the total number of positive predictions (i.e., the number of true positives plus the number of false positives)

Returns:

  • (Float) 


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# File 'lib/oci/ai_language/models/entity_metrics.rb', line 21

def precision
  @precision
end

#recall ⇒ Float

[Required] Measures the model's ability to predict actual positive classes. It is the ratio between the predicted true positives and what was actually tagged. The recall metric reveals how many of the predicted classes are correct.

Returns:

  • (Float) 


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# File 'lib/oci/ai_language/models/entity_metrics.rb', line 25

def recall
  @recall
end

Class Method Details

.attribute_map ⇒ Object

Attribute mapping from ruby-style variable name to JSON key.



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# File 'lib/oci/ai_language/models/entity_metrics.rb', line 28

def self.attribute_map
  {
    # rubocop:disable Style/SymbolLiteral
    'label': :'label',
    'f1': :'f1',
    'precision': :'precision',
    'recall': :'recall'
    # rubocop:enable Style/SymbolLiteral
  }
end

.swagger_types ⇒ Object

Attribute type mapping.



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# File 'lib/oci/ai_language/models/entity_metrics.rb', line 40

def self.swagger_types
  {
    # rubocop:disable Style/SymbolLiteral
    'label': :'String',
    'f1': :'Float',
    'precision': :'Float',
    'recall': :'Float'
    # rubocop:enable Style/SymbolLiteral
  }
end

Instance Method Details

#==(other) ⇒ Object

Checks equality by comparing each attribute.

Parameters:

  • other (Object) —

    the other object to be compared



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# File 'lib/oci/ai_language/models/entity_metrics.rb', line 83

def ==(other)
  return true if equal?(other)

  self.class == other.class &&
    label == other.label &&
    f1 == other.f1 &&
    precision == other.precision &&
    recall == other.recall
end

#build_from_hash(attributes) ⇒ Object

Builds the object from hash

Parameters:

  • attributes (Hash) —

    Model attributes in the form of hash

Returns:

  • (Object) —

    Returns the model itself



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# File 'lib/oci/ai_language/models/entity_metrics.rb', line 116

def build_from_hash(attributes)
  return nil unless attributes.is_a?(Hash)

  self.class.swagger_types.each_pair do |key, type|
    if type =~ /^Array<(.*)>/i
      # check to ensure the input is an array given that the the attribute
      # is documented as an array but the input is not
      if attributes[self.class.attribute_map[key]].is_a?(Array)
        public_method("#{key}=").call(
          attributes[self.class.attribute_map[key]]
            .map { |v| OCI::Internal::Util.convert_to_type(Regexp.last_match(1), v) }
        )
      end
    elsif !attributes[self.class.attribute_map[key]].nil?
      public_method("#{key}=").call(
        OCI::Internal::Util.convert_to_type(type, attributes[self.class.attribute_map[key]])
      )
    end
    # or else data not found in attributes(hash), not an issue as the data can be optional
  end

  self
end

#eql?(other) ⇒ Boolean

Parameters:

  • other (Object) —

    the other object to be compared

Returns:

  • (Boolean)

See Also:

  • `==` method


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# File 'lib/oci/ai_language/models/entity_metrics.rb', line 96

def eql?(other)
  self == other
end

#hash ⇒ Fixnum

Calculates hash code according to all attributes.

Returns:

  • (Fixnum) —

    Hash code



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# File 'lib/oci/ai_language/models/entity_metrics.rb', line 105

def hash
  [label, f1, precision, recall].hash
end

#to_hash ⇒ Hash

Returns the object in the form of hash

Returns:

  • (Hash) —

    Returns the object in the form of hash



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# File 'lib/oci/ai_language/models/entity_metrics.rb', line 149

def to_hash
  hash = {}
  self.class.attribute_map.each_pair do |attr, param|
    value = public_method(attr).call
    next if value.nil? && !instance_variable_defined?("@#{attr}")

    hash[param] = _to_hash(value)
  end
  hash
end

#to_s ⇒ String

Returns the string representation of the object

Returns:

  • (String) —

    String presentation of the object



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# File 'lib/oci/ai_language/models/entity_metrics.rb', line 143

def to_s
  to_hash.to_s
end