2015-06-23 23:05:46 +00:00
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# 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_6
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#
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class Analyze
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include Google::Apis::Core::Hashable
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# Description of the data the model was trained on.
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# Corresponds to the JSON property `dataDescription`
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# @return [Google::Apis::PredictionV1_6::Analyze::DataDescription]
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attr_accessor :data_description
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# List of errors with the data.
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# Corresponds to the JSON property `errors`
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# @return [Array<Hash<String,String>>]
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attr_accessor :errors
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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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# Description of the model.
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# Corresponds to the JSON property `modelDescription`
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# @return [Google::Apis::PredictionV1_6::Analyze::ModelDescription]
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attr_accessor :model_description
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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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@data_description = args[:data_description] if args.key?(:data_description)
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@errors = args[:errors] if args.key?(:errors)
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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_description = args[:model_description] if args.key?(:model_description)
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@self_link = args[:self_link] if args.key?(:self_link)
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end
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# Description of the data the model was trained on.
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class DataDescription
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include Google::Apis::Core::Hashable
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# Description of the input features in the data set.
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# Corresponds to the JSON property `features`
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# @return [Array<Google::Apis::PredictionV1_6::Analyze::DataDescription::Feature>]
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attr_accessor :features
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# Description of the output value or label.
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# Corresponds to the JSON property `outputFeature`
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# @return [Google::Apis::PredictionV1_6::Analyze::DataDescription::OutputFeature]
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attr_accessor :output_feature
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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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@features = args[:features] if args.key?(:features)
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@output_feature = args[:output_feature] if args.key?(:output_feature)
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end
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#
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class Feature
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include Google::Apis::Core::Hashable
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# Description of the categorical values of this feature.
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# Corresponds to the JSON property `categorical`
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# @return [Google::Apis::PredictionV1_6::Analyze::DataDescription::Feature::Categorical]
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attr_accessor :categorical
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# The feature index.
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# Corresponds to the JSON property `index`
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# @return [String]
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attr_accessor :index
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# Description of the numeric values of this feature.
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# Corresponds to the JSON property `numeric`
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# @return [Google::Apis::PredictionV1_6::Analyze::DataDescription::Feature::Numeric]
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attr_accessor :numeric
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# Description of multiple-word text values of this feature.
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# Corresponds to the JSON property `text`
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# @return [Google::Apis::PredictionV1_6::Analyze::DataDescription::Feature::Text]
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attr_accessor :text
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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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@categorical = args[:categorical] if args.key?(:categorical)
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@index = args[:index] if args.key?(:index)
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@numeric = args[:numeric] if args.key?(:numeric)
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@text = args[:text] if args.key?(:text)
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end
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# Description of the categorical values of this feature.
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class Categorical
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include Google::Apis::Core::Hashable
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# Number of categorical values for this feature in the data.
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# Corresponds to the JSON property `count`
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# @return [String]
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attr_accessor :count
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# List of all the categories for this feature in the data set.
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# Corresponds to the JSON property `values`
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# @return [Array<Google::Apis::PredictionV1_6::Analyze::DataDescription::Feature::Categorical::Value>]
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attr_accessor :values
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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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@count = args[:count] if args.key?(:count)
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@values = args[:values] if args.key?(:values)
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end
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#
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class Value
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include Google::Apis::Core::Hashable
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# Number of times this feature had this value.
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# Corresponds to the JSON property `count`
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# @return [String]
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attr_accessor :count
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# The category name.
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# Corresponds to the JSON property `value`
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# @return [String]
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attr_accessor :value
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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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@count = args[:count] if args.key?(:count)
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@value = args[:value] if args.key?(:value)
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end
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end
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end
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# Description of the numeric values of this feature.
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class Numeric
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include Google::Apis::Core::Hashable
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# Number of numeric values for this feature in the data set.
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# Corresponds to the JSON property `count`
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# @return [String]
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attr_accessor :count
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# Mean of the numeric values of this feature in the data set.
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# Corresponds to the JSON property `mean`
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# @return [String]
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attr_accessor :mean
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# Variance of the numeric values of this feature in the data set.
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# Corresponds to the JSON property `variance`
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# @return [String]
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attr_accessor :variance
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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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@count = args[:count] if args.key?(:count)
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@mean = args[:mean] if args.key?(:mean)
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@variance = args[:variance] if args.key?(:variance)
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end
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end
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# Description of multiple-word text values of this feature.
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class Text
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include Google::Apis::Core::Hashable
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# Number of multiple-word text values for this feature.
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# Corresponds to the JSON property `count`
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# @return [String]
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attr_accessor :count
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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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@count = args[:count] if args.key?(:count)
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end
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end
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end
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# Description of the output value or label.
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class OutputFeature
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include Google::Apis::Core::Hashable
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# Description of the output values in the data set.
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# Corresponds to the JSON property `numeric`
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# @return [Google::Apis::PredictionV1_6::Analyze::DataDescription::OutputFeature::Numeric]
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attr_accessor :numeric
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# Description of the output labels in the data set.
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# Corresponds to the JSON property `text`
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# @return [Array<Google::Apis::PredictionV1_6::Analyze::DataDescription::OutputFeature::Text>]
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attr_accessor :text
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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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@numeric = args[:numeric] if args.key?(:numeric)
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@text = args[:text] if args.key?(:text)
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end
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# Description of the output values in the data set.
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class Numeric
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include Google::Apis::Core::Hashable
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# Number of numeric output values in the data set.
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# Corresponds to the JSON property `count`
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# @return [String]
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attr_accessor :count
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# Mean of the output values in the data set.
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# Corresponds to the JSON property `mean`
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# @return [String]
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attr_accessor :mean
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# Variance of the output values in the data set.
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# Corresponds to the JSON property `variance`
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# @return [String]
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attr_accessor :variance
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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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@count = args[:count] if args.key?(:count)
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@mean = args[:mean] if args.key?(:mean)
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@variance = args[:variance] if args.key?(:variance)
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end
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end
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#
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class Text
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include Google::Apis::Core::Hashable
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# Number of times the output label occurred in the data set.
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# Corresponds to the JSON property `count`
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# @return [String]
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attr_accessor :count
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# The output label.
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# Corresponds to the JSON property `value`
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# @return [String]
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attr_accessor :value
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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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@count = args[:count] if args.key?(:count)
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@value = args[:value] if args.key?(:value)
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end
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end
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end
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end
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# Description of the model.
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class ModelDescription
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include Google::Apis::Core::Hashable
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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,String>>]
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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,String>]
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attr_accessor :confusion_matrix_row_totals
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# Basic information about the model.
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# Corresponds to the JSON property `modelinfo`
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# @return [Google::Apis::PredictionV1_6::Insert2]
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attr_accessor :modelinfo
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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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@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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@modelinfo = args[:modelinfo] if args.key?(:modelinfo)
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end
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end
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end
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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_6::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
|
|
|
|
|
|
|
|
def initialize(**args)
|
|
|
|
update!(**args)
|
|
|
|
end
|
|
|
|
|
|
|
|
# Update properties of this object
|
|
|
|
def update!(**args)
|
2016-01-29 22:32:46 +00:00
|
|
|
@csv_instance = args[:csv_instance] if args.key?(:csv_instance)
|
2015-06-23 23:05:46 +00:00
|
|
|
end
|
|
|
|
end
|
|
|
|
end
|
|
|
|
|
|
|
|
#
|
|
|
|
class Insert
|
|
|
|
include Google::Apis::Core::Hashable
|
|
|
|
|
|
|
|
# The unique name for the predictive model.
|
|
|
|
# Corresponds to the JSON property `id`
|
|
|
|
# @return [String]
|
|
|
|
attr_accessor :id
|
|
|
|
|
|
|
|
# Type of predictive model (classification or regression).
|
|
|
|
# Corresponds to the JSON property `modelType`
|
|
|
|
# @return [String]
|
|
|
|
attr_accessor :model_type
|
|
|
|
|
|
|
|
# The Id of the model to be copied over.
|
|
|
|
# Corresponds to the JSON property `sourceModel`
|
|
|
|
# @return [String]
|
|
|
|
attr_accessor :source_model
|
|
|
|
|
|
|
|
# Google storage location of the training data file.
|
|
|
|
# Corresponds to the JSON property `storageDataLocation`
|
|
|
|
# @return [String]
|
|
|
|
attr_accessor :storage_data_location
|
|
|
|
|
|
|
|
# Google storage location of the preprocessing pmml file.
|
|
|
|
# Corresponds to the JSON property `storagePMMLLocation`
|
|
|
|
# @return [String]
|
|
|
|
attr_accessor :storage_pmml_location
|
|
|
|
|
|
|
|
# Google storage location of the pmml model file.
|
|
|
|
# Corresponds to the JSON property `storagePMMLModelLocation`
|
|
|
|
# @return [String]
|
|
|
|
attr_accessor :storage_pmml_model_location
|
|
|
|
|
|
|
|
# Instances to train model on.
|
|
|
|
# Corresponds to the JSON property `trainingInstances`
|
|
|
|
# @return [Array<Google::Apis::PredictionV1_6::Insert::TrainingInstance>]
|
|
|
|
attr_accessor :training_instances
|
|
|
|
|
|
|
|
# A class weighting function, which allows the importance weights for class
|
|
|
|
# labels 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)
|
2016-01-29 22:32:46 +00:00
|
|
|
@id = args[:id] if args.key?(:id)
|
|
|
|
@model_type = args[:model_type] if args.key?(:model_type)
|
|
|
|
@source_model = args[:source_model] if args.key?(:source_model)
|
|
|
|
@storage_data_location = args[:storage_data_location] if args.key?(:storage_data_location)
|
|
|
|
@storage_pmml_location = args[:storage_pmml_location] if args.key?(:storage_pmml_location)
|
|
|
|
@storage_pmml_model_location = args[:storage_pmml_model_location] if args.key?(:storage_pmml_model_location)
|
|
|
|
@training_instances = args[:training_instances] if args.key?(:training_instances)
|
|
|
|
@utility = args[:utility] if args.key?(:utility)
|
2015-06-23 23:05:46 +00:00
|
|
|
end
|
|
|
|
|
|
|
|
#
|
|
|
|
class TrainingInstance
|
|
|
|
include Google::Apis::Core::Hashable
|
|
|
|
|
|
|
|
# The input features for this instance.
|
|
|
|
# Corresponds to the JSON property `csvInstance`
|
|
|
|
# @return [Array<Object>]
|
|
|
|
attr_accessor :csv_instance
|
|
|
|
|
|
|
|
# The generic output value - could be regression or class label.
|
|
|
|
# Corresponds to the JSON property `output`
|
|
|
|
# @return [String]
|
|
|
|
attr_accessor :output
|
|
|
|
|
|
|
|
def initialize(**args)
|
|
|
|
update!(**args)
|
|
|
|
end
|
|
|
|
|
|
|
|
# Update properties of this object
|
|
|
|
def update!(**args)
|
2016-01-29 22:32:46 +00:00
|
|
|
@csv_instance = args[:csv_instance] if args.key?(:csv_instance)
|
|
|
|
@output = args[:output] if args.key?(:output)
|
2015-06-23 23:05:46 +00:00
|
|
|
end
|
|
|
|
end
|
|
|
|
end
|
|
|
|
|
|
|
|
#
|
|
|
|
class Insert2
|
|
|
|
include Google::Apis::Core::Hashable
|
|
|
|
|
|
|
|
# Insert time of the model (as a RFC 3339 timestamp).
|
|
|
|
# Corresponds to the JSON property `created`
|
|
|
|
# @return [DateTime]
|
|
|
|
attr_accessor :created
|
|
|
|
|
|
|
|
# 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_6::Insert2::ModelInfo]
|
|
|
|
attr_accessor :model_info
|
|
|
|
|
|
|
|
# Type of predictive model (CLASSIFICATION or REGRESSION).
|
|
|
|
# Corresponds to the JSON property `modelType`
|
|
|
|
# @return [String]
|
|
|
|
attr_accessor :model_type
|
|
|
|
|
|
|
|
# A URL to re-request this resource.
|
|
|
|
# Corresponds to the JSON property `selfLink`
|
|
|
|
# @return [String]
|
|
|
|
attr_accessor :self_link
|
|
|
|
|
|
|
|
# Google storage location of the training data file.
|
|
|
|
# Corresponds to the JSON property `storageDataLocation`
|
|
|
|
# @return [String]
|
|
|
|
attr_accessor :storage_data_location
|
|
|
|
|
|
|
|
# Google storage location of the preprocessing pmml file.
|
|
|
|
# Corresponds to the JSON property `storagePMMLLocation`
|
|
|
|
# @return [String]
|
|
|
|
attr_accessor :storage_pmml_location
|
|
|
|
|
|
|
|
# Google storage location of the pmml model file.
|
|
|
|
# Corresponds to the JSON property `storagePMMLModelLocation`
|
|
|
|
# @return [String]
|
|
|
|
attr_accessor :storage_pmml_model_location
|
|
|
|
|
|
|
|
# Training completion time (as a RFC 3339 timestamp).
|
|
|
|
# Corresponds to the JSON property `trainingComplete`
|
|
|
|
# @return [DateTime]
|
|
|
|
attr_accessor :training_complete
|
|
|
|
|
|
|
|
# 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
|
|
|
|
|
|
|
|
def initialize(**args)
|
|
|
|
update!(**args)
|
|
|
|
end
|
|
|
|
|
|
|
|
# Update properties of this object
|
|
|
|
def update!(**args)
|
2016-01-29 22:32:46 +00:00
|
|
|
@created = args[:created] if args.key?(:created)
|
|
|
|
@id = args[:id] if args.key?(:id)
|
|
|
|
@kind = args[:kind] if args.key?(:kind)
|
|
|
|
@model_info = args[:model_info] if args.key?(:model_info)
|
|
|
|
@model_type = args[:model_type] if args.key?(:model_type)
|
|
|
|
@self_link = args[:self_link] if args.key?(:self_link)
|
|
|
|
@storage_data_location = args[:storage_data_location] if args.key?(:storage_data_location)
|
|
|
|
@storage_pmml_location = args[:storage_pmml_location] if args.key?(:storage_pmml_location)
|
|
|
|
@storage_pmml_model_location = args[:storage_pmml_model_location] if args.key?(:storage_pmml_model_location)
|
|
|
|
@training_complete = args[:training_complete] if args.key?(:training_complete)
|
|
|
|
@training_status = args[:training_status] if args.key?(:training_status)
|
2015-06-23 23:05:46 +00:00
|
|
|
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 [String]
|
|
|
|
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 [String]
|
|
|
|
attr_accessor :classification_accuracy
|
|
|
|
|
|
|
|
# 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 [String]
|
|
|
|
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 valid data instances used in the trained model.
|
|
|
|
# Corresponds to the JSON property `numberInstances`
|
|
|
|
# @return [String]
|
|
|
|
attr_accessor :number_instances
|
|
|
|
|
|
|
|
# Number of class labels in the trained model (Categorical models only).
|
|
|
|
# Corresponds to the JSON property `numberLabels`
|
|
|
|
# @return [String]
|
|
|
|
attr_accessor :number_labels
|
|
|
|
|
|
|
|
def initialize(**args)
|
|
|
|
update!(**args)
|
|
|
|
end
|
|
|
|
|
|
|
|
# Update properties of this object
|
|
|
|
def update!(**args)
|
2016-01-29 22:32:46 +00:00
|
|
|
@class_weighted_accuracy = args[:class_weighted_accuracy] if args.key?(:class_weighted_accuracy)
|
|
|
|
@classification_accuracy = args[:classification_accuracy] if args.key?(:classification_accuracy)
|
|
|
|
@mean_squared_error = args[:mean_squared_error] if args.key?(:mean_squared_error)
|
|
|
|
@model_type = args[:model_type] if args.key?(:model_type)
|
|
|
|
@number_instances = args[:number_instances] if args.key?(:number_instances)
|
|
|
|
@number_labels = args[:number_labels] if args.key?(:number_labels)
|
2015-06-23 23:05:46 +00:00
|
|
|
end
|
|
|
|
end
|
|
|
|
end
|
|
|
|
|
|
|
|
#
|
|
|
|
class List
|
|
|
|
include Google::Apis::Core::Hashable
|
|
|
|
|
|
|
|
# List of models.
|
|
|
|
# Corresponds to the JSON property `items`
|
|
|
|
# @return [Array<Google::Apis::PredictionV1_6::Insert2>]
|
|
|
|
attr_accessor :items
|
|
|
|
|
|
|
|
# What kind of resource this is.
|
|
|
|
# Corresponds to the JSON property `kind`
|
|
|
|
# @return [String]
|
|
|
|
attr_accessor :kind
|
|
|
|
|
|
|
|
# Pagination token to fetch the next page, if one exists.
|
|
|
|
# Corresponds to the JSON property `nextPageToken`
|
|
|
|
# @return [String]
|
|
|
|
attr_accessor :next_page_token
|
|
|
|
|
|
|
|
# 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)
|
2016-01-29 22:32:46 +00:00
|
|
|
@items = args[:items] if args.key?(:items)
|
|
|
|
@kind = args[:kind] if args.key?(:kind)
|
|
|
|
@next_page_token = args[:next_page_token] if args.key?(:next_page_token)
|
|
|
|
@self_link = args[:self_link] if args.key?(:self_link)
|
2015-06-23 23:05:46 +00:00
|
|
|
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 label (Categorical models only).
|
|
|
|
# Corresponds to the JSON property `outputLabel`
|
|
|
|
# @return [String]
|
|
|
|
attr_accessor :output_label
|
|
|
|
|
|
|
|
# A list of class labels with their estimated probabilities (Categorical models
|
|
|
|
# only).
|
|
|
|
# Corresponds to the JSON property `outputMulti`
|
|
|
|
# @return [Array<Google::Apis::PredictionV1_6::Output::OutputMulti>]
|
|
|
|
attr_accessor :output_multi
|
|
|
|
|
|
|
|
# The estimated regression value (Regression models only).
|
|
|
|
# Corresponds to the JSON property `outputValue`
|
2016-02-10 21:57:13 +00:00
|
|
|
# @return [String]
|
2015-06-23 23:05:46 +00:00
|
|
|
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)
|
2016-01-29 22:32:46 +00:00
|
|
|
@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)
|
2015-06-23 23:05:46 +00:00
|
|
|
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 label.
|
|
|
|
# Corresponds to the JSON property `score`
|
|
|
|
# @return [String]
|
|
|
|
attr_accessor :score
|
|
|
|
|
|
|
|
def initialize(**args)
|
|
|
|
update!(**args)
|
|
|
|
end
|
|
|
|
|
|
|
|
# Update properties of this object
|
|
|
|
def update!(**args)
|
2016-01-29 22:32:46 +00:00
|
|
|
@label = args[:label] if args.key?(:label)
|
|
|
|
@score = args[:score] if args.key?(:score)
|
2015-06-23 23:05:46 +00:00
|
|
|
end
|
|
|
|
end
|
|
|
|
end
|
|
|
|
|
|
|
|
#
|
|
|
|
class Update
|
|
|
|
include Google::Apis::Core::Hashable
|
|
|
|
|
|
|
|
# The input features for this instance.
|
|
|
|
# Corresponds to the JSON property `csvInstance`
|
|
|
|
# @return [Array<Object>]
|
|
|
|
attr_accessor :csv_instance
|
|
|
|
|
|
|
|
# The generic output value - could be regression or class label.
|
|
|
|
# Corresponds to the JSON property `output`
|
|
|
|
# @return [String]
|
|
|
|
attr_accessor :output
|
|
|
|
|
|
|
|
def initialize(**args)
|
|
|
|
update!(**args)
|
|
|
|
end
|
|
|
|
|
|
|
|
# Update properties of this object
|
|
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def update!(**args)
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2016-01-29 22:32:46 +00:00
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@csv_instance = args[:csv_instance] if args.key?(:csv_instance)
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@output = args[:output] if args.key?(:output)
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2015-06-23 23:05:46 +00:00
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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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