public AutoFitter(MLContext mlContext, OptimizingMetricInfo metricInfo, AutoFitSettings settings,
TaskKind task, string label, PurposeInference.Column[] puproseOverrides,
IDataView trainData, IDataView validationData, IDebugLogger debugLogger)
{
_debugLogger = debugLogger;
_history = new List <PipelineRunResult>();
_label = label;
_mlContext = mlContext;
_optimizingMetricInfo = metricInfo;
_settings = settings ?? new AutoFitSettings();
_puproseOverrides = puproseOverrides;
_trainData = trainData;
_task = task;
_validationData = validationData;
}
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);
}