337 lines
12 KiB
Ruby
337 lines
12 KiB
Ruby
# Copyright 2015 Google Inc.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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require 'date'
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require 'google/apis/core/base_service'
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require 'google/apis/core/json_representation'
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require 'google/apis/core/hashable'
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require 'google/apis/errors'
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module Google
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module Apis
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module PredictionV1_4
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#
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class Input
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include Google::Apis::Core::Hashable
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# Input to the model for a prediction
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# Corresponds to the JSON property `input`
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# @return [Google::Apis::PredictionV1_4::Input::Input]
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attr_accessor :input
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def initialize(**args)
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update!(**args)
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end
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# Update properties of this object
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def update!(**args)
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@input = args[:input] if args.key?(:input)
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end
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# Input to the model for a prediction
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class Input
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include Google::Apis::Core::Hashable
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# A list of input features, these can be strings or doubles.
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# Corresponds to the JSON property `csvInstance`
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# @return [Array<Object>]
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attr_accessor :csv_instance
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def initialize(**args)
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update!(**args)
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end
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# Update properties of this object
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def update!(**args)
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@csv_instance = args[:csv_instance] if args.key?(:csv_instance)
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end
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end
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end
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#
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class Output
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include Google::Apis::Core::Hashable
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# The unique name for the predictive model.
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# Corresponds to the JSON property `id`
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# @return [String]
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attr_accessor :id
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# What kind of resource this is.
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# Corresponds to the JSON property `kind`
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# @return [String]
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attr_accessor :kind
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# The most likely class label [Categorical models only].
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# Corresponds to the JSON property `outputLabel`
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# @return [String]
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attr_accessor :output_label
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# A list of class labels with their estimated probabilities [Categorical models
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# only].
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# Corresponds to the JSON property `outputMulti`
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# @return [Array<Google::Apis::PredictionV1_4::Output::OutputMulti>]
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attr_accessor :output_multi
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# The estimated regression value [Regression models only].
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# Corresponds to the JSON property `outputValue`
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# @return [Float]
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attr_accessor :output_value
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# A URL to re-request this resource.
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# Corresponds to the JSON property `selfLink`
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# @return [String]
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attr_accessor :self_link
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def initialize(**args)
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update!(**args)
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end
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# Update properties of this object
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def update!(**args)
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@id = args[:id] if args.key?(:id)
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@kind = args[:kind] if args.key?(:kind)
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@output_label = args[:output_label] if args.key?(:output_label)
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@output_multi = args[:output_multi] if args.key?(:output_multi)
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@output_value = args[:output_value] if args.key?(:output_value)
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@self_link = args[:self_link] if args.key?(:self_link)
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end
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#
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class OutputMulti
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include Google::Apis::Core::Hashable
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# The class label.
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# Corresponds to the JSON property `label`
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# @return [String]
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attr_accessor :label
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# The probability of the class label.
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# Corresponds to the JSON property `score`
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# @return [Float]
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attr_accessor :score
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def initialize(**args)
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update!(**args)
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end
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# Update properties of this object
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def update!(**args)
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@label = args[:label] if args.key?(:label)
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@score = args[:score] if args.key?(:score)
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end
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end
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end
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#
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class Training
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include Google::Apis::Core::Hashable
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# Data Analysis.
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# Corresponds to the JSON property `dataAnalysis`
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# @return [Google::Apis::PredictionV1_4::Training::DataAnalysis]
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attr_accessor :data_analysis
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# The unique name for the predictive model.
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# Corresponds to the JSON property `id`
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# @return [String]
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attr_accessor :id
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# What kind of resource this is.
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# Corresponds to the JSON property `kind`
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# @return [String]
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attr_accessor :kind
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# Model metadata.
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# Corresponds to the JSON property `modelInfo`
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# @return [Google::Apis::PredictionV1_4::Training::ModelInfo]
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attr_accessor :model_info
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# A URL to re-request this resource.
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# Corresponds to the JSON property `selfLink`
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# @return [String]
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attr_accessor :self_link
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# Google storage location of the training data file.
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# Corresponds to the JSON property `storageDataLocation`
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# @return [String]
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attr_accessor :storage_data_location
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# Google storage location of the preprocessing pmml file.
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# Corresponds to the JSON property `storagePMMLLocation`
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# @return [String]
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attr_accessor :storage_pmml_location
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# Google storage location of the pmml model file.
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# Corresponds to the JSON property `storagePMMLModelLocation`
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# @return [String]
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attr_accessor :storage_pmml_model_location
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# The current status of the training job. This can be one of following: RUNNING;
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# DONE; ERROR; ERROR: TRAINING JOB NOT FOUND
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# Corresponds to the JSON property `trainingStatus`
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# @return [String]
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attr_accessor :training_status
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# A class weighting function, which allows the importance weights for class
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# labels to be specified [Categorical models only].
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# Corresponds to the JSON property `utility`
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# @return [Array<Hash<String,Float>>]
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attr_accessor :utility
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def initialize(**args)
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update!(**args)
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end
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# Update properties of this object
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def update!(**args)
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@data_analysis = args[:data_analysis] if args.key?(:data_analysis)
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@id = args[:id] if args.key?(:id)
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@kind = args[:kind] if args.key?(:kind)
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@model_info = args[:model_info] if args.key?(:model_info)
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@self_link = args[:self_link] if args.key?(:self_link)
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@storage_data_location = args[:storage_data_location] if args.key?(:storage_data_location)
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@storage_pmml_location = args[:storage_pmml_location] if args.key?(:storage_pmml_location)
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@storage_pmml_model_location = args[:storage_pmml_model_location] if args.key?(:storage_pmml_model_location)
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@training_status = args[:training_status] if args.key?(:training_status)
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@utility = args[:utility] if args.key?(:utility)
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end
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# Data Analysis.
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class DataAnalysis
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include Google::Apis::Core::Hashable
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#
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# Corresponds to the JSON property `warnings`
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# @return [Array<String>]
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attr_accessor :warnings
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def initialize(**args)
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update!(**args)
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end
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# Update properties of this object
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def update!(**args)
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@warnings = args[:warnings] if args.key?(:warnings)
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end
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end
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# Model metadata.
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class ModelInfo
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include Google::Apis::Core::Hashable
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# Estimated accuracy of model taking utility weights into account [Categorical
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# models only].
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# Corresponds to the JSON property `classWeightedAccuracy`
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# @return [Float]
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attr_accessor :class_weighted_accuracy
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# A number between 0.0 and 1.0, where 1.0 is 100% accurate. This is an estimate,
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# based on the amount and quality of the training data, of the estimated
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# prediction accuracy. You can use this is a guide to decide whether the results
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# are accurate enough for your needs. This estimate will be more reliable if
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# your real input data is similar to your training data [Categorical models only]
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# .
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# Corresponds to the JSON property `classificationAccuracy`
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# @return [Float]
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attr_accessor :classification_accuracy
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# An output confusion matrix. This shows an estimate for how this model will do
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# in predictions. This is first indexed by the true class label. For each true
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# class label, this provides a pair `predicted_label, count`, where count is the
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# estimated number of times the model will predict the predicted label given the
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# true label. Will not output if more then 100 classes [Categorical models only].
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# Corresponds to the JSON property `confusionMatrix`
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# @return [Hash<String,Hash<String,Float>>]
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attr_accessor :confusion_matrix
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# A list of the confusion matrix row totals
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# Corresponds to the JSON property `confusionMatrixRowTotals`
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# @return [Hash<String,Float>]
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attr_accessor :confusion_matrix_row_totals
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# An estimated mean squared error. The can be used to measure the quality of the
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# predicted model [Regression models only].
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# Corresponds to the JSON property `meanSquaredError`
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# @return [Float]
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attr_accessor :mean_squared_error
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# Type of predictive model (CLASSIFICATION or REGRESSION)
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# Corresponds to the JSON property `modelType`
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# @return [String]
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attr_accessor :model_type
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# Number of valid data instances used in the trained model.
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# Corresponds to the JSON property `numberInstances`
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# @return [Fixnum]
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attr_accessor :number_instances
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# Number of class labels in the trained model [Categorical models only].
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# Corresponds to the JSON property `numberLabels`
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# @return [Fixnum]
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attr_accessor :number_labels
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def initialize(**args)
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update!(**args)
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end
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# Update properties of this object
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def update!(**args)
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@class_weighted_accuracy = args[:class_weighted_accuracy] if args.key?(:class_weighted_accuracy)
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@classification_accuracy = args[:classification_accuracy] if args.key?(:classification_accuracy)
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@confusion_matrix = args[:confusion_matrix] if args.key?(:confusion_matrix)
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@confusion_matrix_row_totals = args[:confusion_matrix_row_totals] if args.key?(:confusion_matrix_row_totals)
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@mean_squared_error = args[:mean_squared_error] if args.key?(:mean_squared_error)
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@model_type = args[:model_type] if args.key?(:model_type)
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@number_instances = args[:number_instances] if args.key?(:number_instances)
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@number_labels = args[:number_labels] if args.key?(:number_labels)
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end
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end
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end
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#
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class Update
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include Google::Apis::Core::Hashable
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# The input features for this instance
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# Corresponds to the JSON property `csvInstance`
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# @return [Array<Object>]
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attr_accessor :csv_instance
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# The class label of this instance
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# Corresponds to the JSON property `label`
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# @return [String]
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attr_accessor :label
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# The generic output value - could be regression value or class label
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# Corresponds to the JSON property `output`
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# @return [String]
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attr_accessor :output
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def initialize(**args)
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update!(**args)
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end
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# Update properties of this object
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def update!(**args)
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@csv_instance = args[:csv_instance] if args.key?(:csv_instance)
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@label = args[:label] if args.key?(:label)
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@output = args[:output] if args.key?(:output)
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end
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end
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end
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end
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end
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