static void TrainingTest(List<string> tags) { //const string modelFile = "../../data/gene.key.model"; //const string input = "../../data/gene.key"; const string modelFile = "../../data/training/tag.model.trial1"; const string input = "../../data/training/NYT_19980403_parsed.key"; string LoggerFile = "../../Logs/Log_"+DateTime.Now.ToFileTime()+".txt"; const int threadCount = 1; var perceptron = new Perceptron(input, modelFile, tags); perceptron.Train(); perceptron.ReMapFeatureToK(); //perceptron.Dump(); perceptron.MapFeatures.Dump(); perceptron.ReadInputs(); var featureCache = new FeatureCache(perceptron.InputSentences, tags, perceptron.MapFeatures.DictFeaturesToK); featureCache.CreateCache(); var logger = new WriteModel(LoggerFile); var gradient = new ComputeGradient(perceptron.InputSentences, perceptron.TagsList, tags, .1, featureCache, logger); //perceptron.WeightVector.ResetAllToZero(); gradient.RunIterations(perceptron.WeightVector, 10, threadCount); gradient.Dump(modelFile, perceptron.MapFeatures.DictKToFeatures); }
static void TrainingTest(List<string> tags) { //const string modelFile = "../../data/gene.key.model"; //const string input = "../../data/gene.key"; const string modelFile = "../../data/training/tag.model.trial1"; const string input = "../../data/training/NYT_19980403_parsed.key"; var perceptron = new Perceptron(input, modelFile, tags); perceptron.Train(); perceptron.ReMapFeatureToK(); perceptron.Dump(); perceptron.MapFeatures.Dump(); perceptron.ReadInputs(); var featureCache = new FeatureCache(perceptron.InputSentences, tags, perceptron.MapFeatures.DictFeaturesToK); featureCache.CreateCache(); var gradient = new ComputeGradient(perceptron.InputSentences, perceptron.TagsList, tags, .1, featureCache); gradient.RunIterations(perceptron.WeightVector, 10); gradient.Dump(modelFile, perceptron.MapFeatures.DictKToFeatures); }