google_api_big_query v0.13.0 GoogleApi.BigQuery.V2.Model.TrainingOptions View Source
Attributes
- dataSplitColumn (String.t): The column to split data with. This column won't be used as a feature.
- When data_split_method is CUSTOM, the corresponding column should be boolean. The rows with true value tag are eval data, and the false are training data.
- When data_split_method is SEQ, the first DATA_SPLIT_EVAL_FRACTION
rows (from smallest to largest) in the corresponding column are used
as training data, and the rest are eval data. It respects the order
in Orderable data types:
https://cloud.google.com/bigquery/docs/reference/standard-sql/data-types#data-type-properties Defaults to
nil
.
- dataSplitEvalFraction (float()): The fraction of evaluation data over the whole input data. The rest
of data will be used as training data. The format should be double.
Accurate to two decimal places.
Default value is 0.2. Defaults to
nil
. - dataSplitMethod (String.t): The data split type for training and evaluation, e.g. RANDOM. Defaults to
nil
. - distanceType (String.t): [Beta] Distance type for clustering models. Defaults to
nil
. - earlyStop (boolean()): Whether to stop early when the loss doesn't improve significantly
any more (compared to min_relative_progress). Used only for iterative
training algorithms. Defaults to
nil
. - initialLearnRate (float()): Specifies the initial learning rate for the line search learn rate
strategy. Defaults to
nil
. - inputLabelColumns (list(String.t)): Name of input label columns in training data. Defaults to
nil
. - l1Regularization (float()): L1 regularization coefficient. Defaults to
nil
. - l2Regularization (float()): L2 regularization coefficient. Defaults to
nil
. - labelClassWeights (map()): Weights associated with each label class, for rebalancing the
training data. Only applicable for classification models. Defaults to
nil
. - learnRate (float()): Learning rate in training. Used only for iterative training algorithms. Defaults to
nil
. - learnRateStrategy (String.t): The strategy to determine learn rate for the current iteration. Defaults to
nil
. - lossType (String.t): Type of loss function used during training run. Defaults to
nil
. - maxIterations (String.t): The maximum number of iterations in training. Used only for iterative
training algorithms. Defaults to
nil
. - minRelativeProgress (float()): When early_stop is true, stops training when accuracy improvement is
less than 'min_relative_progress'. Used only for iterative training
algorithms. Defaults to
nil
. - modelUri (String.t): [Beta] Google Cloud Storage URI from which the model was imported. Only
applicable for imported models. Defaults to
nil
. - numClusters (String.t): [Beta] Number of clusters for clustering models. Defaults to
nil
. - optimizationStrategy (String.t): Optimization strategy for training linear regression models. Defaults to
nil
. - warmStart (boolean()): Whether to train a model from the last checkpoint. Defaults to
nil
.
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Functions
Unwrap a decoded JSON object into its complex fields.
Link to this section Types
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t()
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t()
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t() :: %GoogleApi.BigQuery.V2.Model.TrainingOptions{
dataSplitColumn: String.t(),
dataSplitEvalFraction: float(),
dataSplitMethod: String.t(),
distanceType: String.t(),
earlyStop: boolean(),
initialLearnRate: float(),
inputLabelColumns: [String.t()],
l1Regularization: float(),
l2Regularization: float(),
labelClassWeights: map(),
learnRate: float(),
learnRateStrategy: String.t(),
lossType: String.t(),
maxIterations: String.t(),
minRelativeProgress: float(),
modelUri: String.t(),
numClusters: String.t(),
optimizationStrategy: String.t(),
warmStart: boolean()
}
t() :: %GoogleApi.BigQuery.V2.Model.TrainingOptions{ dataSplitColumn: String.t(), dataSplitEvalFraction: float(), dataSplitMethod: String.t(), distanceType: String.t(), earlyStop: boolean(), initialLearnRate: float(), inputLabelColumns: [String.t()], l1Regularization: float(), l2Regularization: float(), labelClassWeights: map(), learnRate: float(), learnRateStrategy: String.t(), lossType: String.t(), maxIterations: String.t(), minRelativeProgress: float(), modelUri: String.t(), numClusters: String.t(), optimizationStrategy: String.t(), warmStart: boolean() }
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decode(value, options) View Source
Unwrap a decoded JSON object into its complex fields.