public void SweepablePipeline_Append_SweepableEstimator_Test()
{
var pipeline = new SweepablePipeline();
var concatOption = new ConcatOption()
{
InputColumnNames = new List <string> {
"a", "b", "c"
}.ToArray(),
OutputColumnName = "a",
};
var lgbmOption = new LgbmOption()
{
FeatureColumnName = "Feature",
LabelColumnName = "Label",
};
// pipeline can append a single sweepable estimator
pipeline = pipeline.Append(SweepableEstimatorFactory.CreateConcatenate(concatOption));
// pipeline can append muliple sweepable estimators.
pipeline = pipeline.Append(SweepableEstimatorFactory.CreateLightGbmBinary(lgbmOption), SweepableEstimatorFactory.CreateConcatenate(concatOption));
// pipeline can append sweepable pipelines mixed with sweepble estimators
pipeline = pipeline.Append(SweepableEstimatorFactory.CreateConcatenate(concatOption), pipeline);
// pipeline can append sweepable pipelines.
pipeline = pipeline.Append(pipeline, pipeline);
Approvals.Verify(JsonSerializer.Serialize(pipeline, _jsonSerializerOptions));
}
public static SweepablePipeline ToPipeline(this SweepablePipelineDataContract pipelineContract, MLContext context)
{
var sweepablePipeline = new SweepablePipeline();
foreach (var node in pipelineContract.Estimators)
{
sweepablePipeline.Append(node.Select(n => context.AutoML().Serializable().Factory.CreateSweepableEstimator(n)).ToArray());
}
return(sweepablePipeline);
}
public SweepablePipeline BuildPipeline(MLContext context, IEnumerable <Column> columns)
{
var sweepablePipeline = new SweepablePipeline();
foreach (var column in columns)
{
switch (column.ColumnPurpose)
{
case ColumnPurpose.NumericFeature:
sweepablePipeline.Append(this.GetSuggestedNumericColumnTransformers(context, column).ToArray());
break;
case ColumnPurpose.CategoricalFeature:
sweepablePipeline.Append(this.GetSuggestedCatagoricalColumnTransformers(context, column).ToArray());
break;
case ColumnPurpose.TextFeature:
sweepablePipeline.Append(this.GetSuggestedTextColumnTransformers(context, column).ToArray());
break;
case ColumnPurpose.Label:
sweepablePipeline.Append(this.GetSuggestedLabelColumnTransformers(context, column).ToArray());
break;
default:
break;
}
}
var featureColumns = columns.Where(c => c.ColumnPurpose == ColumnPurpose.CategoricalFeature ||
c.ColumnPurpose == ColumnPurpose.NumericFeature ||
c.ColumnPurpose == ColumnPurpose.TextFeature)
.Select(c => c.Name)
.ToArray();
if (this.PipelineBuilderOption.IsUsingSingleFeatureTrainer)
{
sweepablePipeline.Append(context.AutoML().Serializable().Transformer.Concatnate(featureColumns, "_FEATURE"));
var labelColumn = columns.Where(c => c.ColumnPurpose == ColumnPurpose.Label).First();
sweepablePipeline.Append(this.GetSuggestedSingleFeatureTrainers(context, labelColumn, "_FEATURE").ToArray());
}
return(sweepablePipeline);
}