public YearBornBot()
{
this.network = (FeedforwardNetwork)SerializeObject
.Load(Config.FILENAME_WHENBORN_NET);
this.histogram = (WordHistogram)SerializeObject
.Load(Config.FILENAME_HISTOGRAM);
}
public void RemoveCommon(WordHistogram other)
{
foreach (HistogramElement element in other.Sorted)
{
HistogramElement e = this.Get(element.Word);
if (e == null)
{
continue;
}
this.sorted.Remove(e);
this.histogram.Remove(element.Word);
}
}
public void Process()
{
this.network = NetworkUtil.CreateNetwork();
Console.WriteLine("Preparing training sets...");
this.common = new CommonWords(Config.FILENAME_COMMON_WORDS);
this.histogramGood = new WordHistogram(this.common);
this.histogramBad = new WordHistogram(this.common);
// load the good words
this.histogramGood.BuildFromFile(Config.FILENAME_GOOD_TRAINING_TEXT);
this.histogramGood.BuildComplete();
// load the bad words
this.histogramBad.BuildFromFile(Config.FILENAME_BAD_TRAINING_TEXT);
this.histogramBad.BuildComplete();
// remove low scoring words
this.histogramGood
.RemoveBelow((int)this.histogramGood.CalculateMean());
this.histogramBad.RemovePercent(0.99);
// remove common words
this.histogramGood.RemoveCommon(this.histogramBad);
this.histogramGood.Trim(Config.INPUT_SIZE);
this.goodAnalysis = new AnalyzeSentences(this.histogramGood,
Config.INPUT_SIZE);
this.badAnalysis = new AnalyzeSentences(this.histogramGood,
Config.INPUT_SIZE);
this.goodAnalysis.Process(this.trainingSet, 0.9,
Config.FILENAME_GOOD_TRAINING_TEXT);
this.badAnalysis.Process(this.trainingSet, 0.1,
Config.FILENAME_BAD_TRAINING_TEXT);
this.sampleCount = this.trainingSet.Ideal.Count;
Console.WriteLine("Processing " + this.sampleCount + " training sets.");
AllocateTrainingSets();
CopyTrainingSets();
TrainNetworkBackpropBackprop();
SerializeObject.Save(Config.FILENAME_WHENBORN_NET, this.network);
SerializeObject.Save(Config.FILENAME_HISTOGRAM, this.histogramGood);
Console.WriteLine("Training complete.");
}
public void Process()
{
this.network = NetworkUtil.CreateNetwork();
Console.WriteLine("Preparing training sets...");
this.common = new CommonWords(Config.FILENAME_COMMON_WORDS);
this.histogramGood = new WordHistogram(this.common);
this.histogramBad = new WordHistogram(this.common);
// load the good words
this.histogramGood.BuildFromFile(Config.FILENAME_GOOD_TRAINING_TEXT);
this.histogramGood.BuildComplete();
// load the bad words
this.histogramBad.BuildFromFile(Config.FILENAME_BAD_TRAINING_TEXT);
this.histogramBad.BuildComplete();
// remove low scoring words
this.histogramGood
.RemoveBelow((int)this.histogramGood.CalculateMean());
this.histogramBad.RemovePercent(0.99);
// remove common words
this.histogramGood.RemoveCommon(this.histogramBad);
this.histogramGood.Trim(Config.INPUT_SIZE);
this.goodAnalysis = new AnalyzeSentences(this.histogramGood,
Config.INPUT_SIZE);
this.badAnalysis = new AnalyzeSentences(this.histogramGood,
Config.INPUT_SIZE);
this.goodAnalysis.Process(this.trainingSet, 0.9,
Config.FILENAME_GOOD_TRAINING_TEXT);
this.badAnalysis.Process(this.trainingSet, 0.1,
Config.FILENAME_BAD_TRAINING_TEXT);
this.sampleCount = this.trainingSet.Ideal.Count;
Console.WriteLine("Processing " + this.sampleCount + " training sets.");
AllocateTrainingSets();
CopyTrainingSets();
TrainNetworkBackpropBackprop();
SerializeObject.Save(Config.FILENAME_WHENBORN_NET, this.network);
SerializeObject.Save(Config.FILENAME_HISTOGRAM, this.histogramGood);
Console.WriteLine("Training complete.");
}
public AnalyzeSentences(WordHistogram histogram, int size)
{
this.histogram = histogram;
}
public void RemoveCommon(WordHistogram other)
{
foreach (HistogramElement element in other.Sorted )
{
HistogramElement e = this.Get(element.Word);
if (e == null)
{
continue;
}
this.sorted.Remove(e);
this.histogram.Remove(element.Word);
}
}
public AnalyzeSentences(WordHistogram histogram, int size)
{
this.histogram = histogram;
}
