protected override Schema.DetachedColumn[] GetOutputColumnsCore()
{
var info = new Schema.DetachedColumn[_parent.Outputs.Length];
for (int i = 0; i < _parent.Outputs.Length; i++)
info[i] = new Schema.DetachedColumn(_parent.Outputs[i], _parent.OutputTypes[i], null);
return info;
}
private protected override Schema.DetachedColumn[] GetOutputColumnsCore()
{
var infos = new Schema.DetachedColumn[2];
infos[L1Col] = new Schema.DetachedColumn(L1, NumberType.R8, null);
infos[L2Col] = new Schema.DetachedColumn(L2, NumberType.R8, null);
return(infos);
}
public override Schema.DetachedColumn[] GetOutputColumns()
{
var infos = new Schema.DetachedColumn[2];
infos[L1Col] = new Schema.DetachedColumn(L1, NumberType.R8, null);
infos[L2Col] = new Schema.DetachedColumn(L2, NumberType.R8, null);
return(infos);
}
public Schema.DetachedColumn[] GetOutputColumns()
{
var meta = new MetadataBuilder();
meta.AddSlotNames(_parent._outputLength, GetSlotNames);
var info = new Schema.DetachedColumn[1];
info[0] = new Schema.DetachedColumn(_parent.OutputColumnName, new VectorType(NumberType.R8, _parent._outputLength), meta.GetMetadata());
return(info);
}
private protected override Schema.DetachedColumn[] GetOutputColumnsCore()
{
var infos = new Schema.DetachedColumn[5];
infos[LabelOutput] = new Schema.DetachedColumn(LabelCol, _labelType, _labelMetadata);
infos[ScoreOutput] = new Schema.DetachedColumn(ScoreCol, _scoreType, _scoreMetadata);
infos[L1Output] = new Schema.DetachedColumn(L1, NumberType.R8, null);
infos[L2Output] = new Schema.DetachedColumn(L2, NumberType.R8, null);
infos[DistCol] = new Schema.DetachedColumn(Dist, NumberType.R8, null);
return(infos);
}
protected override Schema.DetachedColumn[] GetOutputColumnsCore()
{
var result = new Schema.DetachedColumn[_parent.ColumnPairs.Length];
for (int i = 0; i < _parent.ColumnPairs.Length; i++)
{
InputSchema.TryGetColumnIndex(_parent.ColumnPairs[i].input, out int colIndex);
Host.Assert(colIndex >= 0);
result[i] = new Schema.DetachedColumn(_parent.ColumnPairs[i].output, _types[i], null);
}
return result;
}
protected override Schema.DetachedColumn[] GetOutputColumnsCore()
{
var result = new Schema.DetachedColumn[_parent.ColumnPairs.Length];
for (int i = 0; i < _parent.ColumnPairs.Length; i++)
{
var builder = new MetadataBuilder();
builder.Add(InputSchema[ColMapNewToOld[i]].Metadata, x => x == MetadataUtils.Kinds.KeyValues || x == MetadataUtils.Kinds.IsNormalized);
result[i] = new Schema.DetachedColumn(_parent.ColumnPairs[i].outputColumnName, _types[i], builder.GetMetadata());
}
return(result);
}
protected override Schema.DetachedColumn[] GetOutputColumnsCore()
{
var result = new Schema.DetachedColumn[_parent.ColumnPairs.Length];
for (int i = 0; i < _parent.ColumnPairs.Length; i++)
{
var meta = new MetadataBuilder();
meta.Add(InputSchema[ColMapNewToOld[i]].Metadata, name => name == MetadataUtils.Kinds.SlotNames);
result[i] = new Schema.DetachedColumn(_parent.ColumnPairs[i].output, _types[i], meta.GetMetadata());
}
return(result);
}
protected override Schema.DetachedColumn[] GetOutputColumnsCore()
{
var result = new Schema.DetachedColumn[_parent.ColumnPairs.Length];
for (int i = 0; i < _parent.ColumnPairs.Length; i++)
{
var builder = new MetadataBuilder();
AddMetadata(i, builder);
result[i] = new Schema.DetachedColumn(_parent.ColumnPairs[i].output, _type, builder.GetMetadata());
}
return(result);
}
/// <summary>
/// For PCA, the transform equation is y=U^Tx, where "^T" denotes matrix transpose, x is an 1-D vector (i.e., the input column), and U=[u_1, ..., u_PcaNum]
/// is a n-by-PcaNum matrix. The symbol u_k is the k-th largest (in terms of the associated eigenvalue) eigenvector of (1/m)*\sum_{i=1}^m x_ix_i^T,
/// where x_i is the whitened column at the i-th row and we have m rows in the training data.
/// For ZCA, the transform equation is y = US^{-1/2}U^Tx, where U=[u_1, ..., u_n] (we retain all eigenvectors) and S is a diagonal matrix whose i-th
/// diagonal element is the eigenvalues of u_i. The first U^Tx rotates x to another linear space (bases are u_1, ..., u_n), then S^{-1/2} is applied
/// to ensure unit variance, and finally we rotate the scaled result back to the original space using U (note that UU^T is identity matrix so U is
/// the inverse rotation of U^T).
/// </summary>
protected override Schema.DetachedColumn[] GetOutputColumnsCore()
{
var result = new Schema.DetachedColumn[_parent.ColumnPairs.Length];
for (int iinfo = 0; iinfo < _parent.ColumnPairs.Length; iinfo++)
{
InputSchema.TryGetColumnIndex(_parent.ColumnPairs[iinfo].input, out int colIndex);
Host.Assert(colIndex >= 0);
var info = _parent._columns[iinfo];
ColumnType outType = (info.Kind == WhiteningKind.Pca && info.PcaNum > 0) ? new VectorType(NumberType.Float, info.PcaNum) : _srcTypes[iinfo];
result[iinfo] = new Schema.DetachedColumn(_parent.ColumnPairs[iinfo].output, outType, null);
}
return(result);
}
internal static Schema.DetachedColumn[] GetSchemaColumns(InternalSchemaDefinition schemaDefn)
{
Contracts.AssertValue(schemaDefn);
var columns = new Schema.DetachedColumn[schemaDefn.Columns.Length];
for (int i = 0; i < columns.Length; i++)
{
var col = schemaDefn.Columns[i];
var meta = new MetadataBuilder();
foreach (var kvp in col.Metadata)
{
meta.Add(kvp.Value.Kind, kvp.Value.MetadataType, kvp.Value.GetGetterDelegate());
}
columns[i] = new Schema.DetachedColumn(col.ColumnName, col.ColumnType, meta.GetMetadata());
}
return(columns);
}
protected override Schema.DetachedColumn[] GetOutputColumnsCore()
{
var result = new Schema.DetachedColumn[_parent.ColumnPairs.Length];
for (int iinfo = 0; iinfo < _infos.Length; iinfo++)
{
InputSchema.TryGetColumnIndex(_infos[iinfo].Input, out int colIndex);
Host.Assert(colIndex >= 0);
var builder = new MetadataBuilder();
builder.Add(InputSchema[colIndex].Metadata, x => x == MetadataUtils.Kinds.SlotNames);
ValueGetter <bool> getter = (ref bool dst) =>
{
dst = true;
};
builder.Add(MetadataUtils.Kinds.IsNormalized, BoolType.Instance, getter);
result[iinfo] = new Schema.DetachedColumn(_infos[iinfo].Output, _infos[iinfo].OutputType, builder.GetMetadata());
}
return(result);
}
public override Schema.DetachedColumn[] GetOutputColumns()
{
var infos = new Schema.DetachedColumn[3];
infos[ClusterIdCol] = new Schema.DetachedColumn(ClusterId, _types[ClusterIdCol], null);
var slotNamesType = new VectorType(TextType.Instance, _numClusters);
var sortedClusters = new MetadataBuilder();
sortedClusters.AddSlotNames(slotNamesType.VectorSize, CreateSlotNamesGetter(_numClusters, "Cluster"));
var builder = new MetadataBuilder();
builder.AddSlotNames(slotNamesType.VectorSize, CreateSlotNamesGetter(_numClusters, "Score"));
infos[SortedClusterCol] = new Schema.DetachedColumn(SortedClusters, _types[SortedClusterCol], sortedClusters.GetMetadata());
infos[SortedClusterScoreCol] = new Schema.DetachedColumn(SortedClusterScores, _types[SortedClusterScoreCol], builder.GetMetadata());
return(infos);
}
