public static (PipelineRunResult[] allPipelines, PipelineRunResult bestPipeline) Fit(IDataView trainData,
IDataView validationData, string label, InferredColumn[] inferredColumns, AutoFitSettings settings,
TaskKind task, OptimizingMetric metric, IDebugLogger debugLogger)
{
// hack: init new MLContext
var mlContext = new MLContext();
// infer pipelines
var optimizingMetricfInfo = new OptimizingMetricInfo(metric);
var autoFitter = new AutoFitter(mlContext, optimizingMetricfInfo, settings, task,
label, ToInternalColumnPurposes(inferredColumns),
trainData, validationData, debugLogger);
var allPipelines = autoFitter.Fit(1);
var bestScore = allPipelines.Max(p => p.Score);
var bestPipeline = allPipelines.First(p => p.Score == bestScore);
return(allPipelines, bestPipeline);
}
public static (PipelineRunResult[] allPipelines, PipelineRunResult bestPipeline) Fit(IDataView trainData,
IDataView validationData, string label, AutoFitSettings settings, TaskKind task, OptimizingMetric metric,
IEnumerable <(string, ColumnPurpose)> purposeOverrides, IDebugLogger debugLogger)
public OptimizingMetricInfo(OptimizingMetric optimizingMetric)
{
Name = optimizingMetric.ToString();
IsMaximizing = !_minimizingMetrics.Contains(optimizingMetric);
}
