private static IDataView ApplyKeyToVec(List <KeyToVectorTransform.Column> ktv, IDataView viewTrain, IHost host)
{
Contracts.AssertValueOrNull(ktv);
Contracts.AssertValue(viewTrain);
Contracts.AssertValue(host);
if (Utils.Size(ktv) > 0)
{
// Instead of simply using KeyToVector, we are jumping to some hoops here to do the right thing in a very common case
// when the user has slightly different key values between the training and testing set.
// The solution is to apply KeyToValue, then Term using the terms from the key metadata of the original key column
// and finally the KeyToVector transform.
viewTrain = new KeyToValueTransform(host,
new KeyToValueTransform.Arguments()
{
Column = ktv
.Select(c => new KeyToValueTransform.Column()
{
Name = c.Name, Source = c.Source
})
.ToArray()
},
viewTrain);
viewTrain = new Data.TermTransform(host,
new Data.TermTransform.Arguments()
{
Column = ktv
.Select(c => new Data.TermTransform.Column()
{
Name = c.Name, Source = c.Name, Terms = GetTerms(viewTrain, c.Source)
})
.ToArray(),
TextKeyValues = true
},
viewTrain);
viewTrain = new KeyToVectorTransform(host,
new KeyToVectorTransform.Arguments()
{
Column = ktv
.Select(c => new KeyToVectorTransform.Column()
{
Name = c.Name, Source = c.Name
})
.ToArray(),
Bag = false
},
viewTrain);
}
return(viewTrain);
}
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.GetColumnType(labelCol);
if (labelType.IsKey || labelType.IsBool)
{
var nop = NopTransform.CreateIfNeeded(env, input.Data);
return(new CommonOutputs.TransformOutput {
Model = new TransformModel(env, nop, input.Data), OutputData = nop
});
}
var args = new Data.TermTransform.Arguments()
{
Column = new[]
{
new Data.TermTransform.Column()
{
Name = input.LabelColumn,
Source = input.LabelColumn,
TextKeyValues = input.TextKeyValues,
Sort = Data.TermTransform.SortOrder.Value
}
}
};
var xf = new Data.TermTransform(host, args, input.Data);
return(new CommonOutputs.TransformOutput {
Model = new TransformModel(env, xf, input.Data), OutputData = xf
});
}
