public static CommonOutputs.TransformOutput SelectColumns(IHostEnvironment env, ColumnSelectingTransformer.Arguments input)
{
Contracts.CheckValue(env, nameof(env));
var host = env.Register("SelectColumns");
host.CheckValue(input, nameof(input));
EntryPointUtils.CheckInputArgs(host, input);
var xf = new ColumnSelectingTransformer(env, input.KeepColumns, input.DropColumns, input.KeepHidden, input.IgnoreMissing).Transform(input.Data);
return(new CommonOutputs.TransformOutput {
Model = new TransformModelImpl(env, xf, input.Data), OutputData = xf
});
}
public static CommonOutputs.TransformOutput ConcatColumns(IHostEnvironment env, ColumnConcatenatingTransformer.Arguments input)
{
Contracts.CheckValue(env, nameof(env));
var host = env.Register("ConcatColumns");
host.CheckValue(input, nameof(input));
EntryPointUtils.CheckInputArgs(host, input);
var xf = ColumnConcatenatingTransformer.Create(env, input, input.Data);
return(new CommonOutputs.TransformOutput {
Model = new TransformModelImpl(env, xf, input.Data), OutputData = xf
});
}
public static CommonOutputs.TransformOutput FilterByRange(IHostEnvironment env, RangeFilter.Options input)
{
Contracts.CheckValue(env, nameof(env));
var host = env.Register(RangeFilter.LoaderSignature);
host.CheckValue(input, nameof(input));
EntryPointUtils.CheckInputArgs(host, input);
var xf = new RangeFilter(host, input, input.Data);
return(new CommonOutputs.TransformOutput {
Model = new TransformModelImpl(env, xf, input.Data), OutputData = xf
});
}
public static Output ScoreUsingTransform(IHostEnvironment env, InputTransformScorer input)
{
Contracts.CheckValue(env, nameof(env));
var host = env.Register("ScoreModelUsingTransform");
host.CheckValue(input, nameof(input));
EntryPointUtils.CheckInputArgs(host, input);
return
(new Output
{
ScoredData = input.TransformModel.Apply(env, input.Data),
ScoringTransform = null
});
}
public static CommonOutputs.SummaryOutput Summarize(IHostEnvironment env, SummarizePredictor.Input input)
{
Contracts.CheckValue(env, nameof(env));
var host = env.Register("LinearRegressionPredictor");
host.CheckValue(input, nameof(input));
EntryPointUtils.CheckInputArgs(host, input);
RoleMappedData rmd;
IPredictor predictor;
input.PredictorModel.PrepareData(host, new EmptyDataView(host, input.PredictorModel.TransformModel.InputSchema), out rmd, out predictor);
var output = new CommonOutputs.SummaryOutput();
output.Summary = GetSummaryAndStats(host, predictor, rmd.Schema, out output.Stats);
return(output);
}
public static CommonOutputs.TransformOutput PrepareClassificationLabel(IHostEnvironment env, ClassificationLabelInput input)
{
Contracts.CheckValue(env, nameof(env));
var host = env.Register("PrepareClassificationLabel");
host.CheckValue(input, nameof(input));
EntryPointUtils.CheckInputArgs(host, input);
var labelCol = input.Data.Schema.GetColumnOrNull(input.LabelColumn);
if (!labelCol.HasValue)
{
throw host.ExceptSchemaMismatch(nameof(input), "predicted label", input.LabelColumn);
}
var labelType = labelCol.Value.Type;
if (labelType is KeyType || labelType is BooleanDataViewType)
{
var nop = NopTransform.CreateIfNeeded(env, input.Data);
return(new CommonOutputs.TransformOutput {
Model = new TransformModelImpl(env, nop, input.Data), OutputData = nop
});
}
var args = new ValueToKeyMappingTransformer.Options()
{
Columns = new[]
{
new ValueToKeyMappingTransformer.Column()
{
Name = input.LabelColumn,
Source = input.LabelColumn,
TextKeyValues = input.TextKeyValues,
Sort = ValueToKeyMappingEstimator.KeyOrdinality.ByValue
}
}
};
var xf = ValueToKeyMappingTransformer.Create(host, args, input.Data);
return(new CommonOutputs.TransformOutput {
Model = new TransformModelImpl(env, xf, input.Data), OutputData = xf
});
}
public static CommonOutputs.TransformOutput PrepareClassificationLabel(IHostEnvironment env, ClassificationLabelInput input)
{
Contracts.CheckValue(env, nameof(env));
var host = env.Register("PrepareClassificationLabel");
host.CheckValue(input, nameof(input));
EntryPointUtils.CheckInputArgs(host, input);
int labelCol;
if (!input.Data.Schema.TryGetColumnIndex(input.LabelColumn, out labelCol))
{
throw host.Except($"Column '{input.LabelColumn}' not found.");
}
var labelType = input.Data.Schema[labelCol].Type;
if (labelType.IsKey || labelType.IsBool)
{
var nop = NopTransform.CreateIfNeeded(env, input.Data);
return(new CommonOutputs.TransformOutput {
Model = new TransformModelImpl(env, nop, input.Data), OutputData = nop
});
}
var args = new ValueToKeyMappingTransformer.Arguments()
{
Column = new[]
{
new ValueToKeyMappingTransformer.Column()
{
Name = input.LabelColumn,
Source = input.LabelColumn,
TextKeyValues = input.TextKeyValues,
Sort = ValueToKeyMappingTransformer.SortOrder.Value
}
}
};
var xf = ValueToKeyMappingTransformer.Create(host, args, input.Data);
return(new CommonOutputs.TransformOutput {
Model = new TransformModelImpl(env, xf, input.Data), OutputData = xf
});
}
public static CommonOutputs.TransformOutput PrepareRegressionLabel(IHostEnvironment env, RegressionLabelInput input)
{
Contracts.CheckValue(env, nameof(env));
var host = env.Register("PrepareRegressionLabel");
host.CheckValue(input, nameof(input));
EntryPointUtils.CheckInputArgs(host, input);
int labelCol;
if (!input.Data.Schema.TryGetColumnIndex(input.LabelColumn, out labelCol))
{
throw host.Except($"Column '{input.LabelColumn}' not found.");
}
var labelType = input.Data.Schema[labelCol].Type;
if (labelType == NumberType.R4 || !labelType.IsNumber)
{
var nop = NopTransform.CreateIfNeeded(env, input.Data);
return(new CommonOutputs.TransformOutput {
Model = new TransformModelImpl(env, nop, input.Data), OutputData = nop
});
}
var args = new TypeConvertingTransformer.Arguments()
{
Column = new[]
{
new TypeConvertingTransformer.Column()
{
Name = input.LabelColumn,
Source = input.LabelColumn,
ResultType = DataKind.R4
}
}
};
var xf = new TypeConvertingTransformer(host, new TypeConvertingTransformer.ColumnInfo(input.LabelColumn, input.LabelColumn, DataKind.R4)).Transform(input.Data);
return(new CommonOutputs.TransformOutput {
Model = new TransformModelImpl(env, xf, input.Data), OutputData = xf
});
}
public static CombineTransformModelsOutput CombineTransformModels(IHostEnvironment env, CombineTransformModelsInput input)
{
Contracts.CheckValue(env, nameof(env));
var host = env.Register("CombineTransformModels");
host.CheckValue(input, nameof(input));
EntryPointUtils.CheckInputArgs(host, input);
host.CheckNonEmpty(input.Models, nameof(input.Models));
TransformModel model = input.Models[input.Models.Length - 1];
for (int i = input.Models.Length - 2; i >= 0; i--)
{
model = model.Apply(env, input.Models[i]);
}
return(new CombineTransformModelsOutput {
OutputModel = model
});
}
public static CommonOutputs.TransformOutput ConvertPredictedLabel(IHostEnvironment env, PredictedLabelInput input)
{
Contracts.CheckValue(env, nameof(env));
var host = env.Register("ConvertPredictedLabel");
host.CheckValue(input, nameof(input));
EntryPointUtils.CheckInputArgs(host, input);
var predictedLabelCol = input.Data.Schema.GetColumnOrNull(input.PredictedLabelColumn);
if (!predictedLabelCol.HasValue)
throw host.ExceptSchemaMismatch(nameof(input), "PredictedLabel",input.PredictedLabelColumn);
var predictedLabelType = predictedLabelCol.Value.Type;
if (predictedLabelType is NumberType || predictedLabelType is BoolType)
{
var nop = NopTransform.CreateIfNeeded(env, input.Data);
return new CommonOutputs.TransformOutput { Model = new TransformModelImpl(env, nop, input.Data), OutputData = nop };
}
var xf = new KeyToValueMappingTransformer(host, input.PredictedLabelColumn).Transform(input.Data);
return new CommonOutputs.TransformOutput { Model = new TransformModelImpl(env, xf, input.Data), OutputData = xf };
}
public static CommonOutputs.TransformOutput PrepareFeatures(IHostEnvironment env, FeatureCombinerInput input)
{
const string featureCombiner = "FeatureCombiner";
Contracts.CheckValue(env, nameof(env));
var host = env.Register(featureCombiner);
host.CheckValue(input, nameof(input));
EntryPointUtils.CheckInputArgs(host, input);
using (var ch = host.Start(featureCombiner))
{
var viewTrain = input.Data;
var rms = new RoleMappedSchema(viewTrain.Schema, input.GetRoles());
var feats = rms.GetColumns(RoleMappedSchema.ColumnRole.Feature);
if (Utils.Size(feats) == 0)
throw ch.Except("No feature columns specified");
var featNames = new HashSet<string>();
var concatNames = new List<KeyValuePair<string, string>>();
List<TypeConvertingTransformer.ColumnInfo> cvt;
int errCount;
var ktv = ConvertFeatures(feats.ToArray(), featNames, concatNames, ch, out cvt, out errCount);
Contracts.Assert(featNames.Count > 0);
Contracts.Assert(concatNames.Count == featNames.Count);
if (errCount > 0)
throw ch.Except("Encountered {0} invalid training column(s)", errCount);
viewTrain = ApplyConvert(cvt, viewTrain, host);
viewTrain = ApplyKeyToVec(ktv, viewTrain, host);
// REVIEW: What about column name conflicts? Eg, what if someone uses the group id column
// (a key type) as a feature column. We convert that column to a vector so it is no longer valid
// as a group id. That's just one example - you get the idea.
string nameFeat = DefaultColumnNames.Features;
viewTrain = ColumnConcatenatingTransformer.Create(host,
new ColumnConcatenatingTransformer.TaggedArguments()
{
Column =
new[] { new ColumnConcatenatingTransformer.TaggedColumn() { Name = nameFeat, Source = concatNames.ToArray() } }
},
viewTrain);
return new CommonOutputs.TransformOutput { Model = new TransformModelImpl(env, viewTrain, input.Data), OutputData = viewTrain };
}
}
public static Output Split(IHostEnvironment env, Input input)
{
Contracts.CheckValue(env, nameof(env));
var host = env.Register(ModuleName);
host.CheckValue(input, nameof(input));
EntryPointUtils.CheckInputArgs(host, input);
var data = input.Data;
var stratCol = SplitUtils.CreateStratificationColumn(host, ref data, input.StratificationColumn);
int n = input.NumFolds;
var output = new Output
{
TrainData = new IDataView[n],
TestData = new IDataView[n]
};
// Construct per-fold datasets.
double fraction = 1.0 / n;
for (int i = 0; i < n; i++)
{
var trainData = new RangeFilter(host,
new RangeFilter.Options {
Column = stratCol, Min = i * fraction, Max = (i + 1) * fraction, Complement = true
}, data);
output.TrainData[i] = ColumnSelectingTransformer.CreateDrop(host, trainData, stratCol);
var testData = new RangeFilter(host,
new RangeFilter.Options {
Column = stratCol, Min = i * fraction, Max = (i + 1) * fraction, Complement = false
}, data);
output.TestData[i] = ColumnSelectingTransformer.CreateDrop(host, testData, stratCol);
}
return(output);
}
