internal FieldAwareFactorizationMachinePredictionTransformer(IHostEnvironment host, FieldAwareFactorizationMachineModelParameters model, DataViewSchema trainSchema,
string[] featureColumns, float threshold = 0f, string thresholdColumn = DefaultColumnNames.Score)
: base(Contracts.CheckRef(host, nameof(host)).Register(nameof(FieldAwareFactorizationMachinePredictionTransformer)), model, trainSchema)
{
Host.CheckNonEmpty(thresholdColumn, nameof(thresholdColumn));
Host.CheckNonEmpty(featureColumns, nameof(featureColumns));
_threshold = threshold;
_thresholdColumn = thresholdColumn;
FeatureColumns = featureColumns;
var featureColumnTypes = new DataViewType[featureColumns.Length];
int i = 0;
foreach (var feat in featureColumns)
{
if (!trainSchema.TryGetColumnIndex(feat, out int col))
{
throw Host.ExceptSchemaMismatch(nameof(featureColumns), "feature", feat);
}
featureColumnTypes[i++] = trainSchema[col].Type;
}
FeatureColumnTypes = featureColumnTypes;
BindableMapper = ScoreUtils.GetSchemaBindableMapper(Host, model);
var schema = GetSchema();
var args = new BinaryClassifierScorer.Arguments {
Threshold = _threshold, ThresholdColumn = _thresholdColumn
};
Scorer = new BinaryClassifierScorer(Host, args, new EmptyDataView(Host, trainSchema), BindableMapper.Bind(Host, schema), schema);
}
private void SetScorer()
{
var schema = new RoleMappedSchema(TrainSchema, LabelColumnName, FeatureColumnName);
var args = new BinaryClassifierScorer.Arguments {
Threshold = Threshold, ThresholdColumn = ThresholdColumn
};
Scorer = new BinaryClassifierScorer(Host, args, new EmptyDataView(Host, TrainSchema), BindableMapper.Bind(Host, schema), schema);
}
public BinaryPredictionTransformer(IHostEnvironment env, TModel model, ISchema inputSchema, string featureColumn,
float threshold = 0f, string thresholdColumn = DefaultColumnNames.Score)
: base(Contracts.CheckRef(env, nameof(env)).Register(nameof(BinaryPredictionTransformer <TModel>)), model, inputSchema, featureColumn)
{
Host.CheckNonEmpty(thresholdColumn, nameof(thresholdColumn));
var schema = new RoleMappedSchema(inputSchema, null, featureColumn);
Threshold = threshold;
ThresholdColumn = thresholdColumn;
var args = new BinaryClassifierScorer.Arguments {
Threshold = Threshold, ThresholdColumn = ThresholdColumn
};
_scorer = new BinaryClassifierScorer(Host, args, new EmptyDataView(Host, inputSchema), BindableMapper.Bind(Host, schema), schema);
}
public BinaryPredictionTransformer(IHostEnvironment env, ModelLoadContext ctx)
: base(Contracts.CheckRef(env, nameof(env)).Register(nameof(BinaryPredictionTransformer <TModel>)), ctx)
{
// *** Binary format ***
// <base info>
// float: scorer threshold
// id of string: scorer threshold column
Threshold = ctx.Reader.ReadSingle();
ThresholdColumn = ctx.LoadString();
var schema = new RoleMappedSchema(TrainSchema, null, FeatureColumn);
var args = new BinaryClassifierScorer.Arguments {
Threshold = Threshold, ThresholdColumn = ThresholdColumn
};
_scorer = new BinaryClassifierScorer(Host, args, new EmptyDataView(Host, TrainSchema), BindableMapper.Bind(Host, schema), schema);
}
internal FieldAwareFactorizationMachinePredictionTransformer(IHostEnvironment host, ModelLoadContext ctx)
: base(Contracts.CheckRef(host, nameof(host)).Register(nameof(FieldAwareFactorizationMachinePredictionTransformer)), ctx)
{
// *** Binary format ***
// <base info>
// ids of strings: feature columns.
// float: scorer threshold
// id of string: scorer threshold column
// count of feature columns. FAFM uses more than one.
int featCount = Model.FieldCount;
var featureColumns = new string[featCount];
var featureColumnTypes = new DataViewType[featCount];
for (int i = 0; i < featCount; i++)
{
featureColumns[i] = ctx.LoadString();
if (!TrainSchema.TryGetColumnIndex(featureColumns[i], out int col))
{
throw Host.ExceptSchemaMismatch(nameof(FeatureColumns), "feature", featureColumns[i]);
}
featureColumnTypes[i] = TrainSchema[col].Type;
}
FeatureColumns = featureColumns;
FeatureColumnTypes = featureColumnTypes;
_threshold = ctx.Reader.ReadSingle();
_thresholdColumn = ctx.LoadString();
BindableMapper = ScoreUtils.GetSchemaBindableMapper(Host, Model);
var schema = GetSchema();
var args = new BinaryClassifierScorer.Arguments {
Threshold = _threshold, ThresholdColumn = _thresholdColumn
};
Scorer = new BinaryClassifierScorer(Host, args, new EmptyDataView(Host, TrainSchema), BindableMapper.Bind(Host, schema), schema);
}
public FieldAwareFactorizationMachinePredictionTransformer(IHostEnvironment host, FieldAwareFactorizationMachinePredictor model, Schema trainSchema,
string[] featureColumns, float threshold = 0f, string thresholdColumn = DefaultColumnNames.Score)
: base(Contracts.CheckRef(host, nameof(host)).Register(nameof(FieldAwareFactorizationMachinePredictionTransformer)), model, trainSchema)
{
Host.CheckNonEmpty(thresholdColumn, nameof(thresholdColumn));
_threshold = threshold;
_thresholdColumn = thresholdColumn;
Host.CheckValue(featureColumns, nameof(featureColumns));
int featCount = featureColumns.Length;
Host.Check(featCount >= 0, "Empty features column.");
FeatureColumns = featureColumns;
FeatureColumnTypes = new ColumnType[featCount];
int i = 0;
foreach (var feat in featureColumns)
{
if (!trainSchema.TryGetColumnIndex(feat, out int col))
{
throw Host.ExceptSchemaMismatch(nameof(featureColumns), RoleMappedSchema.ColumnRole.Feature.Value, feat);
}
FeatureColumnTypes[i++] = trainSchema.GetColumnType(col);
}
BindableMapper = ScoreUtils.GetSchemaBindableMapper(Host, model);
var schema = GetSchema();
var args = new BinaryClassifierScorer.Arguments {
Threshold = _threshold, ThresholdColumn = _thresholdColumn
};
Scorer = new BinaryClassifierScorer(Host, args, new EmptyDataView(Host, trainSchema), BindableMapper.Bind(Host, schema), schema);
}
public BinaryScorerWrapper <TModel> Clone(BinaryClassifierScorer.Arguments scorerArgs)
{
var scorer = _xf as IDataScorerTransform;
return(new BinaryScorerWrapper <TModel>(_env, InnerModel, scorer.Source.Schema, _featureColumn, scorerArgs));
}
private static IDataView MakeScorer(IHostEnvironment env, ISchema schema, string featureColumn, TModel model, BinaryClassifierScorer.Arguments args)
{
var settings = $"Binary{{{CmdParser.GetSettings(env, args, new BinaryClassifierScorer.Arguments())}}}";
var scorerFactorySettings = CmdParser.CreateComponentFactory(
typeof(IComponentFactory <IDataView, ISchemaBoundMapper, RoleMappedSchema, IDataScorerTransform>),
typeof(SignatureDataScorer),
settings);
var bindable = ScoreUtils.GetSchemaBindableMapper(env, model, scorerFactorySettings: scorerFactorySettings);
var edv = new EmptyDataView(env, schema);
var data = new RoleMappedData(edv, "Label", featureColumn, opt: true);
return(new BinaryClassifierScorer(env, args, data.Data, bindable.Bind(env, data.Schema), data.Schema));
}
public BinaryScorerWrapper(IHostEnvironment env, TModel model, ISchema inputSchema, string featureColumn, BinaryClassifierScorer.Arguments args)
: base(env, MakeScorer(env, inputSchema, featureColumn, model, args), model, featureColumn)
{
}
