public SparseMatcher(ISparseDistance distance, IReworder reworder, IReader reader, ITokenizer tokenizer, string encyclopediaFilePath)
{
_distance = distance;
_reader = reader;
_reworder = reworder;
_tokenizer = tokenizer;
_encyclopediaFilePath = encyclopediaFilePath;
}
public static void MetricRun(IReworder reworder, IReader reader, ITokenizer tok, ISparseDistance dist, int nbNeighbours, bool train, bool proba, string questionFilePath, string encyclopediaFilePath, string outFolder)
{
string encyclopediaName = Path.GetFileNameWithoutExtension(encyclopediaFilePath);
string summary = "Metric_" + reworder.GetType().Name + "_" +
reader.GetType().Name + "_" + tok.GetType().Name + "_" + dist.GetType().Name + "_" + nbNeighbours.ToString() + "_" + encyclopediaName;
Console.Write("\n" + summary);
SparseMatcher robot = new SparseMatcher(dist, reworder, reader, tok, encyclopediaFilePath);
string[] answers = robot.Answer(nbNeighbours, questionFilePath, train, proba);
if (train)
{
EvaluateAndPrintScores(questionFilePath, answers);
}
else
{
string[] ids = TextToData.ImportColumn(questionFilePath, 0);
Submissions.Write(answers, ids, outFolder + summary + ".csv");
}
Console.WriteLine();
}
