A folded data set allows you to "fold" the data into several equal(or nearly equal) datasets. You then have the ability to select which fold the dataset will process. This is very useful for crossvalidation. This dataset works off of an underlying dataset. By default there are no folds (fold size 1). Call the fold method to create more folds.
Inheritance: IIndexable
FoldedDataSet Class Documentation
Esempio n. 1
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 /// <summary>
 /// Construct a cross trainer. 
 /// </summary>
 /// <param name="network">The network.</param>
 /// <param name="training">The training data.</param>
 public CrossTraining(BasicNetwork network,
          FoldedDataSet training)
 {
     this.network = network;
     Training = training;
     this.folded = training;
 }
Esempio n. 2
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        /// <summary>
        /// Open an additional dataset.
        /// </summary>
        /// <returns>The dataset.</returns>
        public IEngineIndexableSet OpenAdditional()
        {
            FoldedDataSet folded = new FoldedDataSet(
                (IIndexable)this.underlying.OpenAdditional());

            folded.Owner = this;
            return(folded);
        }
Esempio n. 3
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 /// <summary>
 /// Open an additional dataset.
 /// </summary>
 /// <returns>The dataset.</returns>
 public IEngineIndexableSet OpenAdditional()
 {
     FoldedDataSet folded = new FoldedDataSet(
             (IIndexable)this.underlying.OpenAdditional());
     folded.Owner = this;
     return folded;
 }
Esempio n. 4
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 /// <summary>
 /// Construct an enumerator.
 /// </summary>
 /// <param name="owner">The owner.</param>
 public FoldedEnumerator(FoldedDataSet owner)
 {
     this.owner        = owner;
     this.currentIndex = -1;
 }