/// <summary>
/// Trains a new unsupervised model.
/// </summary>
/// <param name="model">Type of unsupervised model: Skipgram or Cbow.</param>
/// <param name="inputPath">Path to a training set.</param>
/// <param name="outputPath">Path to write the model to (excluding extension).</param>
/// <param name="args">Low-level training arguments.</param>
/// <remarks>Trained model will consist of two files: .bin (main model) and .vec (word vectors).</remarks>
public void Unsupervised(UnsupervisedModel model, string inputPath, string outputPath, UnsupervisedArgs args)
{
ValidatePaths(inputPath, outputPath, args.PretrainedVectors);
args.model = (ModelName)model;
var argsStruct = _mapper.Map <FastTextArgsStruct>(args);
CheckForErrors(Train(_fastText, inputPath, outputPath, argsStruct, new AutotuneArgsStruct(), args.LabelPrefix, args.PretrainedVectors, false));
_maxLabelLen = 0;
ModelPath = AdjustPath(outputPath, false);
}
/// <summary>
/// Trains a new unsupervised model.
/// </summary>
/// <param name="model">Type of unsupervised model: Skipgram or Cbow.</param>
/// <param name="inputPath">Path to a training set.</param>
/// <param name="outputPath">Path to write the model to (excluding extension).</param>
/// <remarks>Trained model will consist of two files: .bin (main model) and .vec (word vectors).</remarks>
public void Unsupervised(UnsupervisedModel model, string inputPath, string outputPath)
{
Unsupervised(model, inputPath, outputPath, new UnsupervisedArgs());
}
