/// <summary>
/// Select the best run from an enumeration of experiment runs.
/// </summary>
/// <param name="results">Enumeration of AutoML experiment run results.</param>
/// <param name="metric">Metric to consider when selecting the best run.</param>
/// <param name="groupIdColumnName">Name for the GroupId column.</param>
/// <returns>The best experiment run.</returns>
public static RunDetail <RankingMetrics> Best(this IEnumerable <RunDetail <RankingMetrics> > results, RankingMetric metric = RankingMetric.Ndcg, string groupIdColumnName = "GroupId")
{
var metricsAgent = new RankingMetricsAgent(null, metric, groupIdColumnName);
var isMetricMaximizing = new OptimizingMetricInfo(metric).IsMaximizing;
return(BestResultUtil.GetBestRun(results, metricsAgent, isMetricMaximizing));
}
/// <summary>
/// Select the best run from an enumeration of experiment runs.
/// </summary>
/// <param name="results">Enumeration of AutoML experiment run results.</param>
/// <param name="metric">Metric to consider when selecting the best run.</param>
/// <param name="optimizationMetricTruncationLevel">Maximum truncation level for computing (N)DCG. Defaults to 10.</param>
/// <returns>The best experiment run.</returns>
public static RunDetail <RankingMetrics> Best(this IEnumerable <RunDetail <RankingMetrics> > results, RankingMetric metric = RankingMetric.Ndcg, uint optimizationMetricTruncationLevel = 10)
{
var metricsAgent = new RankingMetricsAgent(null, metric, optimizationMetricTruncationLevel);
var isMetricMaximizing = new OptimizingMetricInfo(metric).IsMaximizing;
return(BestResultUtil.GetBestRun(results, metricsAgent, isMetricMaximizing));
}
/// <summary>
/// Select the best run from an enumeration of experiment cross validation runs.
/// </summary>
/// <param name="results">Enumeration of AutoML experiment cross validation run results.</param>
/// <param name="metric">Metric to consider when selecting the best run.</param>
/// <returns>The best experiment run.</returns>
public static CrossValidationRunDetail <RegressionMetrics> Best(this IEnumerable <CrossValidationRunDetail <RegressionMetrics> > results, RegressionMetric metric = RegressionMetric.RSquared)
{
var metricsAgent = new RegressionMetricsAgent(null, metric);
var isMetricMaximizing = new OptimizingMetricInfo(metric).IsMaximizing;
return(BestResultUtil.GetBestRun(results, metricsAgent, isMetricMaximizing));
}
public Experiment(MLContext context,
TaskKind task,
OptimizingMetricInfo metricInfo,
IProgress <TRunDetail> progressCallback,
ExperimentSettings experimentSettings,
IMetricsAgent <TMetrics> metricsAgent,
IEnumerable <TrainerName> trainerAllowList,
DatasetColumnInfo[] datasetColumnInfo,
IRunner <TRunDetail> runner,
IChannel logger)
{
_context = context;
_history = new List <SuggestedPipelineRunDetail>();
_optimizingMetricInfo = metricInfo;
_task = task;
_progressCallback = progressCallback;
_experimentSettings = experimentSettings;
_metricsAgent = metricsAgent;
_trainerAllowList = trainerAllowList;
_modelDirectory = GetModelDirectory(_context.TempFilePath, _experimentSettings.CacheDirectoryName);
_datasetColumnInfo = datasetColumnInfo;
_runner = runner;
_logger = logger;
_experimentTimerExpired = false;
}
public static RunDetail <MulticlassClassificationMetrics> GetBestRun(IEnumerable <RunDetail <MulticlassClassificationMetrics> > results,
MulticlassClassificationMetric metric)
{
var metricsAgent = new MultiMetricsAgent(null, metric);
var metricInfo = new OptimizingMetricInfo(metric);
return(GetBestRun(results, metricsAgent, metricInfo.IsMaximizing));
}
public static RunDetail <RankingMetrics> GetBestRun(IEnumerable <RunDetail <RankingMetrics> > results,
RankingMetric metric, string groupIdColumnName)
{
var metricsAgent = new RankingMetricsAgent(null, metric, groupIdColumnName);
var metricInfo = new OptimizingMetricInfo(metric);
return(GetBestRun(results, metricsAgent, metricInfo.IsMaximizing));
}
public static RunDetail <RankingMetrics> GetBestRun(IEnumerable <RunDetail <RankingMetrics> > results,
RankingMetric metric, uint dcgTruncationLevel)
{
var metricsAgent = new RankingMetricsAgent(null, metric, dcgTruncationLevel);
var metricInfo = new OptimizingMetricInfo(metric);
return(GetBestRun(results, metricsAgent, metricInfo.IsMaximizing));
}
internal ExperimentBase(MLContext context,
IMetricsAgent <TMetrics> metricsAgent,
OptimizingMetricInfo optimizingMetricInfo,
TExperimentSettings settings,
TaskKind task,
IEnumerable <TrainerName> trainerAllowList)
{
Context = context;
MetricsAgent = metricsAgent;
OptimizingMetricInfo = optimizingMetricInfo;
Settings = settings;
_logger = ((IChannelProvider)context).Start("AutoML");
_task = task;
_trainerAllowList = trainerAllowList;
}
public CrossValSummaryRunner(MLContext context,
IDataView[] trainDatasets,
IDataView[] validDatasets,
IMetricsAgent <TMetrics> metricsAgent,
IEstimator <ITransformer> preFeaturizer,
ITransformer[] preprocessorTransforms,
string labelColumn,
OptimizingMetricInfo optimizingMetricInfo,
IChannel logger)
{
_context = context;
_trainDatasets = trainDatasets;
_validDatasets = validDatasets;
_metricsAgent = metricsAgent;
_preFeaturizer = preFeaturizer;
_preprocessorTransforms = preprocessorTransforms;
_labelColumn = labelColumn;
_optimizingMetricInfo = optimizingMetricInfo;
_logger = logger;
_modelInputSchema = trainDatasets[0].Schema;
}