google-api-ruby-client/generated/google/apis/prediction_v1_3/classes.rb

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# Copyright 2015 Google Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
require 'date'
require 'google/apis/core/base_service'
require 'google/apis/core/json_representation'
require 'google/apis/core/hashable'
require 'google/apis/errors'
module Google
module Apis
module PredictionV1_3
#
class Input
include Google::Apis::Core::Hashable
# Input to the model for a prediction
# Corresponds to the JSON property `input`
# @return [Google::Apis::PredictionV1_3::Input::Input]
attr_accessor :input
def initialize(**args)
update!(**args)
end
# Update properties of this object
def update!(**args)
@input = args[:input] if args.key?(:input)
end
# Input to the model for a prediction
class Input
include Google::Apis::Core::Hashable
# A list of input features, these can be strings or doubles.
# Corresponds to the JSON property `csvInstance`
# @return [Array<Object>]
attr_accessor :csv_instance
def initialize(**args)
update!(**args)
end
# Update properties of this object
def update!(**args)
@csv_instance = args[:csv_instance] if args.key?(:csv_instance)
end
end
end
#
class Output
include Google::Apis::Core::Hashable
# The unique name for the predictive model.
# Corresponds to the JSON property `id`
# @return [String]
attr_accessor :id
# What kind of resource this is.
# Corresponds to the JSON property `kind`
# @return [String]
attr_accessor :kind
# The most likely class [Categorical models only].
# Corresponds to the JSON property `outputLabel`
# @return [String]
attr_accessor :output_label
# A list of classes with their estimated probabilities [Categorical models only].
# Corresponds to the JSON property `outputMulti`
# @return [Array<Google::Apis::PredictionV1_3::Output::OutputMulti>]
attr_accessor :output_multi
# The estimated regression value [Regression models only].
# Corresponds to the JSON property `outputValue`
# @return [Float]
attr_accessor :output_value
# A URL to re-request this resource.
# Corresponds to the JSON property `selfLink`
# @return [String]
attr_accessor :self_link
def initialize(**args)
update!(**args)
end
# Update properties of this object
def update!(**args)
@id = args[:id] if args.key?(:id)
@kind = args[:kind] if args.key?(:kind)
@output_label = args[:output_label] if args.key?(:output_label)
@output_multi = args[:output_multi] if args.key?(:output_multi)
@output_value = args[:output_value] if args.key?(:output_value)
@self_link = args[:self_link] if args.key?(:self_link)
end
#
class OutputMulti
include Google::Apis::Core::Hashable
# The class label.
# Corresponds to the JSON property `label`
# @return [String]
attr_accessor :label
# The probability of the class.
# Corresponds to the JSON property `score`
# @return [Float]
attr_accessor :score
def initialize(**args)
update!(**args)
end
# Update properties of this object
def update!(**args)
@label = args[:label] if args.key?(:label)
@score = args[:score] if args.key?(:score)
end
end
end
#
class Training
include Google::Apis::Core::Hashable
# The unique name for the predictive model.
# Corresponds to the JSON property `id`
# @return [String]
attr_accessor :id
# What kind of resource this is.
# Corresponds to the JSON property `kind`
# @return [String]
attr_accessor :kind
# Model metadata.
# Corresponds to the JSON property `modelInfo`
# @return [Google::Apis::PredictionV1_3::Training::ModelInfo]
attr_accessor :model_info
# A URL to re-request this resource.
# Corresponds to the JSON property `selfLink`
# @return [String]
attr_accessor :self_link
# The current status of the training job. This can be one of following: RUNNING;
# DONE; ERROR; ERROR: TRAINING JOB NOT FOUND
# Corresponds to the JSON property `trainingStatus`
# @return [String]
attr_accessor :training_status
# A class weighting function, which allows the importance weights for classes to
# be specified [Categorical models only].
# Corresponds to the JSON property `utility`
# @return [Array<Hash<String,Float>>]
attr_accessor :utility
def initialize(**args)
update!(**args)
end
# Update properties of this object
def update!(**args)
@id = args[:id] if args.key?(:id)
@kind = args[:kind] if args.key?(:kind)
@model_info = args[:model_info] if args.key?(:model_info)
@self_link = args[:self_link] if args.key?(:self_link)
@training_status = args[:training_status] if args.key?(:training_status)
@utility = args[:utility] if args.key?(:utility)
end
# Model metadata.
class ModelInfo
include Google::Apis::Core::Hashable
# Estimated accuracy of model taking utility weights into account [Categorical
# models only].
# Corresponds to the JSON property `classWeightedAccuracy`
# @return [Float]
attr_accessor :class_weighted_accuracy
# A number between 0.0 and 1.0, where 1.0 is 100% accurate. This is an estimate,
# based on the amount and quality of the training data, of the estimated
# prediction accuracy. You can use this is a guide to decide whether the results
# are accurate enough for your needs. This estimate will be more reliable if
# your real input data is similar to your training data [Categorical models only]
# .
# Corresponds to the JSON property `classificationAccuracy`
# @return [Float]
attr_accessor :classification_accuracy
# An output confusion matrix. This shows an estimate for how this model will do
# in predictions. This is first indexed by the true class label. For each true
# class label, this provides a pair `predicted_label, count`, where count is the
# estimated number of times the model will predict the predicted label given the
# true label. Will not output if more then 100 classes [Categorical models only].
# Corresponds to the JSON property `confusionMatrix`
# @return [Hash<String,Hash<String,Float>>]
attr_accessor :confusion_matrix
# A list of the confusion matrix row totals
# Corresponds to the JSON property `confusionMatrixRowTotals`
# @return [Hash<String,Float>]
attr_accessor :confusion_matrix_row_totals
# An estimated mean squared error. The can be used to measure the quality of the
# predicted model [Regression models only].
# Corresponds to the JSON property `meanSquaredError`
# @return [Float]
attr_accessor :mean_squared_error
# Type of predictive model (CLASSIFICATION or REGRESSION)
# Corresponds to the JSON property `modelType`
# @return [String]
attr_accessor :model_type
# Number of classes in the trained model [Categorical models only].
# Corresponds to the JSON property `numberClasses`
# @return [Fixnum]
attr_accessor :number_classes
# Number of valid data instances used in the trained model.
# Corresponds to the JSON property `numberInstances`
# @return [Fixnum]
attr_accessor :number_instances
def initialize(**args)
update!(**args)
end
# Update properties of this object
def update!(**args)
@class_weighted_accuracy = args[:class_weighted_accuracy] if args.key?(:class_weighted_accuracy)
@classification_accuracy = args[:classification_accuracy] if args.key?(:classification_accuracy)
@confusion_matrix = args[:confusion_matrix] if args.key?(:confusion_matrix)
@confusion_matrix_row_totals = args[:confusion_matrix_row_totals] if args.key?(:confusion_matrix_row_totals)
@mean_squared_error = args[:mean_squared_error] if args.key?(:mean_squared_error)
@model_type = args[:model_type] if args.key?(:model_type)
@number_classes = args[:number_classes] if args.key?(:number_classes)
@number_instances = args[:number_instances] if args.key?(:number_instances)
end
end
end
#
class Update
include Google::Apis::Core::Hashable
# The true class label of this instance
# Corresponds to the JSON property `classLabel`
# @return [String]
attr_accessor :class_label
# The input features for this instance
# Corresponds to the JSON property `csvInstance`
# @return [Array<Object>]
attr_accessor :csv_instance
def initialize(**args)
update!(**args)
end
# Update properties of this object
def update!(**args)
@class_label = args[:class_label] if args.key?(:class_label)
@csv_instance = args[:csv_instance] if args.key?(:csv_instance)
end
end
end
end
end