/// <summary>
/// Connects a row classifier
/// </summary>
/// <param name="classifier"></param>
/// <param name="dataTable"></param>
/// <param name="analysis"></param>
/// <param name="name">Optional name to give the node</param>
/// <returns></returns>
public WireBuilder AddClassifier(IRowClassifier classifier, IDataTable dataTable, IDataTableAnalysis analysis = null, string name = null)
{
var node = _factory.CreateClassifier(classifier, dataTable, analysis, name);
_SetNode(node.RowClassifier);
return(SetNewSize(node.OutputSize));
}
/// <summary>
/// Create a row classifier node
/// </summary>
/// <param name="classifier">The classifier for each row</param>
/// <param name="dataTable">The data table that contains the rows to classify (linked by mini batch index)</param>
/// <param name="analysis">Optional data table analysis data</param>
/// <param name="name">Optional name to give the node</param>
/// <returns></returns>
public (INode RowClassifier, int OutputSize) CreateClassifier(IRowClassifier classifier,
IDataTable dataTable, IDataTableAnalysis analysis = null, string name = null)
{
var ret = new RowClassifier(LinearAlgebraProvider, classifier, dataTable,
analysis ?? dataTable.GetAnalysis(), name);
return(ret, ret.OutputSize);
}
//readonly List<IRow> _data = new List<IRow>();
public RowClassifier(ILinearAlgebraProvider lap, IRowClassifier classifier,
IDataTable dataTable, IDataTableAnalysis analysis, string name = null) : base(name)
{
_lap = lap;
_dataTable = dataTable;
_classifier = classifier;
_targetLabel = analysis.ColumnInfo.First(ci => dataTable.Columns[ci.ColumnIndex].IsTarget).
DistinctValues.Select((v, i) => (v.ToString(), i)).ToDictionary(d => d.Item1, d => d.Item2);
}
public IReadOnlyList <RowClassification> Classify(IRowClassifier classifier)
{
var ret = new List <RowClassification>();
_Iterate(row => {
ret.Add(new RowClassification(row, classifier.Classify(row).First()));
return(true);
});
return(ret);
}
public IReadOnlyList <(IRow Row, string Classification)> Classify(IRowClassifier classifier, Action <float> progress = null)
{
var ret = new List <(IRow, string)>();
float total = RowCount;
_Iterate((row, i) => {
var bestClassification = classifier.Classify(row).GetBestClassification();
ret.Add((row, bestClassification));
progress?.Invoke(i / total);
return(true);
});
return(ret);
}
/// <summary>
/// Classifies each row of the data table
/// </summary>
/// <param name="classifier"></param>
/// <param name="dataTable"></param>
/// <returns>A list of rows with their corresponding classifications</returns>
public static IReadOnlyList <(IRow Row, string Classification)> Classifiy(this IRowClassifier classifier, IDataTable dataTable)
{
return(dataTable.Classify(classifier, percentage => Console.Write("\r({0:P}) ", percentage)));
}
