protected CrossTraining(IMLMethod network, FoldedDataSet training) : base(TrainingImplementationType.Iterative) { this._x87a7fc6a72741c2e = network; this.Training = training; this._x3952df2eab48841c = training; }
/// <summary> /// Construct a cross trainer. /// </summary> /// /// <param name="network">The network.</param> /// <param name="training">The training data.</param> protected CrossTraining(IMLMethod network, FoldedDataSet training) : base(TrainingImplementationType.Iterative) { _network = network; Training = training; _folded = training; }
/// <summary> /// Open an additional dataset. /// </summary> /// <returns>The dataset.</returns> public IMLDataSet OpenAdditional() { var folded = new FoldedDataSet(_underlying.OpenAdditional()) { Owner = this }; return(folded); }
public void TestRPROPFolded() { IMLDataSet trainingData = XOR.CreateNoisyXORDataSet(10); BasicNetwork network = NetworkUtil.CreateXORNetworkUntrained(); var folded = new FoldedDataSet(trainingData); IMLTrain train = new ResilientPropagation(network, folded); var trainFolded = new CrossValidationKFold(train, 4); EncogUtility.TrainToError(trainFolded, 0.2); XOR.VerifyXOR((IMLRegression) trainFolded.Method, 0.2); }
/// <summary> /// Open an additional dataset. /// </summary> /// <returns>The dataset.</returns> public IMLDataSet OpenAdditional() { var folded = new FoldedDataSet(_underlying.OpenAdditional()) {Owner = this}; return folded; }
/// <summary> /// Obtain the training set. /// </summary> /// <returns>The training set.</returns> private IMLDataSet ObtainTrainingSet() { String trainingID = Prop.GetPropertyString( ScriptProperties.MlConfigTrainingFile); FileInfo trainingFile = Script.ResolveFilename(trainingID); IMLDataSet trainingSet = EncogUtility.LoadEGB2Memory(trainingFile); if (_kfold > 0) { trainingSet = new FoldedDataSet(trainingSet); } return trainingSet; }
/// <summary> /// Construct an enumerator. /// </summary> /// <param name="owner">The owner.</param> public FoldedEnumerator(FoldedDataSet owner) { _owner = owner; _currentIndex = -1; }
private IMLDataSet x13d6d581f93d9ea3() { IMLDataSet set; string propertyString = base.Prop.GetPropertyString("ML:CONFIG_trainingFile"); FileInfo filename = base.Script.ResolveFilename(propertyString); if (1 != 0) { set = EncogUtility.LoadEGB2Memory(filename); while (this._x33d31451731666c6 > 0) { do { set = new FoldedDataSet(set); } while (-1 == 0); if (-2147483648 != 0) { return set; } } return set; } return set; }