public Create ( int alphabetCardinality, int i ) : object | ||
alphabetCardinality | int | /// Alphabet cardinality. /// |
i | int | /// The dimensionality of the matrix. /// |
리턴 | object |
/// <summary> /// The teach. /// </summary> /// <param name="chain"> /// The chain. /// </param> /// <param name="method"> /// The method. /// </param> public override void Teach(BaseChain chain, TeachingMethod method) { var builder = new MatrixBuilder(); var absoluteMatrix = (IAbsoluteMatrix)builder.Create(chain.Alphabet.Cardinality, Rank); for (int i = 0; i < chain.Alphabet.Cardinality; i++) { int[] temp = new int[1]; temp[0] = chain.Alphabet.IndexOf(chain.Alphabet[i]); absoluteMatrix.Add(temp); } ProbabilityMatrixes[0] = absoluteMatrix.ProbabilityMatrix(); }
/// <summary> /// Teaches markov chain using provided sequence. /// </summary> /// <param name="chain"> /// Sequence used for teaching. /// </param> /// <param name="method"> /// Chain preprocessing method. /// </param> public virtual void Teach(BaseChain chain, TeachingMethod method) { var builder = new MatrixBuilder(); var absMatrix = new IAbsoluteMatrix[HeterogeneityRank + 1]; Alphabet = chain.Alphabet; for (int i = 0; i < HeterogeneityRank + 1; i++) { absMatrix[i] = (IAbsoluteMatrix)builder.Create(Alphabet.Cardinality, Rank); } SpaceReorganizer reorganizer = GetRebuilder(method); chain = (BaseChain)reorganizer.Reorganize(chain); var it = new IteratorStart(chain, Rank, 1); it.Reset(); int k = 0; // filling matrixes while (it.Next()) { ++k; int m = k % (HeterogeneityRank + 1); if (m == 0) { m = HeterogeneityRank + 1; } BaseChain chainToTeach = (BaseChain)it.Current(); var indexedChain = new int[Rank]; for (int i = 0; i < Rank; i++) { indexedChain[i] = chain.Alphabet.IndexOf(chainToTeach[i]); } absMatrix[m - 1].Add(indexedChain); } for (int i = 0; i < HeterogeneityRank + 1; i++) { ProbabilityMatrixes[i] = absMatrix[i].ProbabilityMatrix(); } }