public StringCharFeatures(StringCharFeatures orig) : this(modshogunPINVOKE.new_StringCharFeatures__SWIG_5(StringCharFeatures.getCPtr(orig)), true)
{
if (modshogunPINVOKE.SWIGPendingException.Pending)
{
throw modshogunPINVOKE.SWIGPendingException.Retrieve();
}
}
public static void Main()
{
modshogun.init_shogun_with_defaults();
int degree = 20;
double scale = 1.4;
int size_cache = 10;
int order = 3;
int gap = 0;
bool reverse = false;
String[] fm_train_dna = Load.load_dna("../data/fm_train_dna.dat");
String[] fm_test_dna = Load.load_dna("../data/fm_test_dna.dat");
StringCharFeatures charfeat = new StringCharFeatures(fm_train_dna, EAlphabet.DNA);
StringWordFeatures feats_train = new StringWordFeatures(EAlphabet.DNA);
feats_train.obtain_from_char(charfeat, order - 1, order, gap, reverse);
StringCharFeatures charfeat_test = new StringCharFeatures(fm_test_dna, EAlphabet.DNA);
StringWordFeatures feats_test = new StringWordFeatures(EAlphabet.DNA);
feats_test.obtain_from_char(charfeat_test, order - 1, order, gap, reverse);
MatchWordStringKernel kernel = new MatchWordStringKernel(size_cache, degree);
kernel.set_normalizer(new AvgDiagKernelNormalizer(scale));
kernel.init(feats_train, feats_train);
double[,] km_train = kernel.get_kernel_matrix();
kernel.init(feats_train, feats_test);
double[,] km_test = kernel.get_kernel_matrix();
modshogun.exit_shogun();
}
public static void Main() {
modshogun.init_shogun_with_defaults();
bool reverse = false;
int order = 3;
int gap = 0;
string[] fm_train_dna = Load.load_dna("../data/fm_train_dna.dat");
string[] fm_test_dna = Load.load_dna("../data/fm_test_dna.dat");
StringCharFeatures charfeat = new StringCharFeatures(fm_train_dna, EAlphabet.DNA);
StringUlongFeatures feats_train = new StringUlongFeatures(charfeat.get_alphabet());
feats_train.obtain_from_char(charfeat, order-1, order, gap, reverse);
charfeat = new StringCharFeatures(fm_test_dna, EAlphabet.DNA);
StringUlongFeatures feats_test = new StringUlongFeatures(charfeat.get_alphabet());
feats_test.obtain_from_char(charfeat, order-1, order, gap, reverse);
SortUlongString preproc = new SortUlongString();
preproc.init(feats_train);
feats_train.add_preprocessor(preproc);
feats_train.apply_preprocessor();
feats_test.add_preprocessor(preproc);
feats_test.apply_preprocessor();
CommUlongStringKernel kernel = new CommUlongStringKernel(feats_train, feats_train, false);
double[,] km_train = kernel.get_kernel_matrix();
kernel.init(feats_train, feats_test);
double[,] km_test = kernel.get_kernel_matrix();
modshogun.exit_shogun();
}
public static void Main() {
bool reverse = false;
modshogun.init_shogun_with_defaults();
int order = 3;
int gap = 4;
String[] fm_train_dna = Load.load_dna("../data/fm_train_dna.dat");
StringCharFeatures charfeat = new StringCharFeatures(fm_train_dna, EAlphabet.DNA);
StringWordFeatures feats = new StringWordFeatures(charfeat.get_alphabet());
feats.obtain_from_char(charfeat, order-1, order, gap, reverse);
LinearHMM hmm = new LinearHMM(feats);
hmm.train();
hmm.get_transition_probs();
int num_examples = feats.get_num_vectors();
int num_param = hmm.get_num_model_parameters();
for (int i = 0; i < num_examples; i++)
for(int j = 0; j < num_param; j++) {
hmm.get_log_derivative(j, i);
}
double[] out_likelihood = hmm.get_log_likelihood();
double out_sample = hmm.get_log_likelihood_sample();
}
public LocalAlignmentStringKernel(StringCharFeatures l, StringCharFeatures r, double opening, double extension) : this(modshogunPINVOKE.new_LocalAlignmentStringKernel__SWIG_2(StringCharFeatures.getCPtr(l), StringCharFeatures.getCPtr(r), opening, extension), true)
{
if (modshogunPINVOKE.SWIGPendingException.Pending)
{
throw modshogunPINVOKE.SWIGPendingException.Retrieve();
}
}
public static void Main()
{
modshogun.init_shogun_with_defaults();
bool reverse = false;
int order = 3;
int gap = 0;
String[] fm_train_dna = Load.load_dna("../data/fm_train_dna.dat");
String[] fm_test_dna = Load.load_dna("../data/fm_test_dna.dat");
StringCharFeatures charfeat = new StringCharFeatures(fm_train_dna, EAlphabet.DNA);
StringWordFeatures feats_train = new StringWordFeatures(charfeat.get_alphabet());
feats_train.obtain_from_char(charfeat, order-1, order, gap, false);
charfeat = new StringCharFeatures(fm_test_dna, EAlphabet.DNA);
StringWordFeatures feats_test = new StringWordFeatures(charfeat.get_alphabet());
feats_test.obtain_from_char(charfeat, order-1, order, gap, false);
BinaryLabels labels = new BinaryLabels(Load.load_labels("../data/label_train_dna.dat"));
PluginEstimate pie = new PluginEstimate();
pie.set_labels(labels);
pie.set_features(feats_train);
pie.train();
SalzbergWordStringKernel kernel = new SalzbergWordStringKernel(feats_train, feats_train, pie, labels);
double[,] km_train = kernel.get_kernel_matrix();
kernel.init(feats_train, feats_test);
pie.set_features(feats_test);
BinaryLabels.obtain_from_generic(pie.apply()).get_labels();
double[,] km_test=kernel.get_kernel_matrix();
modshogun.exit_shogun();
}
public RegulatoryModulesStringKernel(StringCharFeatures lstr, StringCharFeatures rstr, WordFeatures lpos, WordFeatures rpos, double width, int degree, int shift, int window) : this(modshogunPINVOKE.new_RegulatoryModulesStringKernel__SWIG_3(StringCharFeatures.getCPtr(lstr), StringCharFeatures.getCPtr(rstr), WordFeatures.getCPtr(lpos), WordFeatures.getCPtr(rpos), width, degree, shift, window), true)
{
if (modshogunPINVOKE.SWIGPendingException.Pending)
{
throw modshogunPINVOKE.SWIGPendingException.Retrieve();
}
}
static void Main(string[] argv)
{
modshogun.init_shogun_with_defaults();
int order = 3;
int gap = 0;
bool reverse = false;
bool use_sign = false;
string[] fm_train_dna = Load.load_dna("../data/fm_train_dna.dat");
string[] fm_test_dna = Load.load_dna("../data/fm_test_dna.dat");
StringCharFeatures charfeat = new StringCharFeatures(DNA);
charfeat.set_features(fm_train_dna);
StringWordFeatures feats_train = new StringWordFeatures(charfeat.get_alphabet());
feats_train.obtain_from_char(charfeat, order-1, order, gap, reverse);
SortWordString preproc = new SortWordString();
preproc.init(feats_train);
feats_train.add_preprocessor(preproc);
feats_train.apply_preprocessor();
StringCharFeatures charfeat_test = new StringCharFeatures(DNA);
charfeat_test.set_features(fm_test_dna);
StringWordFeatures feats_test = new StringWordFeatures(charfeat.get_alphabet());
feats_test.obtain_from_char(charfeat_test, order-1, order, gap, reverse);
feats_test.add_preprocessor(preproc);
feats_test.apply_preprocessor();
CommWordStringKernel kernel = new CommWordStringKernel(feats_train, feats_train, use_sign);
DoubleMatrix km_train = kernel.get_kernel_matrix();
kernel.init(feats_train, feats_test);
DoubleMatrix km_test = kernel.get_kernel_matrix();
modshogun.exit_shogun();
}
public SparseSpatialSampleStringKernel(StringCharFeatures l, StringCharFeatures r) : this(modshogunPINVOKE.new_SparseSpatialSampleStringKernel__SWIG_1(StringCharFeatures.getCPtr(l), StringCharFeatures.getCPtr(r)), true)
{
if (modshogunPINVOKE.SWIGPendingException.Pending)
{
throw modshogunPINVOKE.SWIGPendingException.Retrieve();
}
}
internal static DoubleMatrix run(IList para)
{
int degree = 20;
modshogun.init_shogun_with_defaults();
double C = (double)((double?)para[0]);
double epsilon = (double)((double?)para[1]);
int num_threads = (int)((int?)para[2]);
string[] fm_train_dna = {"CGCACGTACGTAGCTCGAT", "CGACGTAGTCGTAGTCGTA", "CGACGGGGGGGGGGTCGTA", "CGACCTAGTCGTAGTCGTA", "CGACCACAGTTATATAGTA", "CGACGTAGTCGTAGTCGTA", "CGACGTAGTTTTTTTCGTA", "CGACGTAGTCGTAGCCCCA", "CAAAAAAAAAAAAAAAATA", "CGACGGGGGGGGGGGCGTA"};
string[] fm_test_dna = {"AGCACGTACGTAGCTCGAT", "AGACGTAGTCGTAGTCGTA", "CAACGGGGGGGGGGTCGTA", "CGACCTAGTCGTAGTCGTA", "CGAACACAGTTATATAGTA", "CGACCTAGTCGTAGTCGTA", "CGACGTGGGGTTTTTCGTA", "CGACGTAGTCCCAGCCCCA", "CAAAAAAAAAAAACCAATA", "CGACGGCCGGGGGGGCGTA"};
StringCharFeatures feats_train = new StringCharFeatures(fm_train_dna, DNA);
StringCharFeatures feats_test = new StringCharFeatures(fm_test_dna, DNA);
WeightedDegreeStringKernel kernel = new WeightedDegreeStringKernel(feats_train, feats_train, degree);
double[][] label_train_dna = { new double[] { -1, -1, -1, -1, -1, 1, 1, 1, 1, 1 } };
Labels labels = new Labels(new DoubleMatrix(label_train_dna));
SVMLight svm = new SVMLight(C, kernel, labels);
svm.set_qpsize(3);
svm.set_linear_term(new DoubleMatrix(new double[][] {{-1,-2,-3,-4,-5,-6,-7,-8,-7,-6}}));
svm.set_epsilon(epsilon);
//svm.parallel.set_num_threads(num_threads);
svm.train();
kernel.init(feats_train, feats_test);
DoubleMatrix @out = svm.apply().get_labels();
modshogun.exit_shogun();
return @out;
}
static void Main(string[] argv)
{
modshogun.init_shogun_with_defaults();
int degree = 3;
int C = 1;
string[] fm_train_dna = {"CGCACGTACGTAGCTCGAT", "CGACGTAGTCGTAGTCGTA", "CGACGGGGGGGGGGTCGTA", "CGACCTAGTCGTAGTCGTA", "CGACCACAGTTATATAGTA", "CGACGTAGTCGTAGTCGTA", "CGACGTAGTTTTTTTCGTA", "CGACGTAGTCGTAGCCCCA", "CAAAAAAAAAAAAAAAATA", "CGACGGGGGGGGGGGCGTA"};
string[] fm_test_dna = {"AGCACGTACGTAGCTCGAT", "AGACGTAGTCGTAGTCGTA", "CAACGGGGGGGGGGTCGTA", "CGACCTAGTCGTAGTCGTA", "CGAACACAGTTATATAGTA", "CGACCTAGTCGTAGTCGTA", "CGACGTGGGGTTTTTCGTA", "CGACGTAGTCCCAGCCCCA", "CAAAAAAAAAAAACCAATA", "CGACGGCCGGGGGGGCGTA"};
StringCharFeatures feats_train = new StringCharFeatures(fm_train_dna, DNA);
StringCharFeatures feats_test = new StringCharFeatures(fm_test_dna, DNA);
WeightedDegreeStringKernel kernel = new WeightedDegreeStringKernel(feats_train, feats_train, degree);
double[][] label_train_dna = { new double[] { -1, -1, -1, -1, -1, 1, 1, 1, 1, 1 } };
Labels labels = new Labels(new DoubleMatrix(label_train_dna));
SVMLight svm = new SVMLight(C, kernel, labels);
svm.train();
DomainAdaptationSVM dasvm = new DomainAdaptationSVM(C, kernel, labels, svm, 1.0);
dasvm.train();
DoubleMatrix @out = dasvm.apply(feats_test).get_labels();
modshogun.exit_shogun();
}
internal static ArrayList run(IList para)
{
bool reverse = false;
modshogun.init_shogun_with_defaults();
int degree = (int)((int?)para[0]);
string[] fm_train_dna = Load.load_dna("../data/fm_train_dna.dat");
string[] fm_test_dna = Load.load_dna("../data/fm_test_dna.dat");
StringCharFeatures feats_train = new StringCharFeatures(fm_train_dna, DNA);
StringCharFeatures feats_test = new StringCharFeatures(fm_test_dna, DNA);
PolyMatchStringKernel kernel = new PolyMatchStringKernel(feats_train, feats_train, degree, true);
DoubleMatrix km_train = kernel.get_kernel_matrix();
kernel.init(feats_train, feats_test);
DoubleMatrix km_test =kernel.get_kernel_matrix();
ArrayList result = new ArrayList();
result.Add(km_train);
result.Add(km_test);
result.Add(kernel);
modshogun.exit_shogun();
return result;
}
public WeightedDegreeStringKernel(StringCharFeatures l, StringCharFeatures r, int degree) : this(modshogunPINVOKE.new_WeightedDegreeStringKernel__SWIG_4(StringCharFeatures.getCPtr(l), StringCharFeatures.getCPtr(r), degree), true)
{
if (modshogunPINVOKE.SWIGPendingException.Pending)
{
throw modshogunPINVOKE.SWIGPendingException.Retrieve();
}
}
public static void Main()
{
modshogun.init_shogun_with_defaults();
bool reverse = false;
int order = 3;
int gap = 0;
int degree = 2;
string[] fm_train_dna = Load.load_dna("../data/fm_train_dna.dat");
string[] fm_test_dna = Load.load_dna("../data/fm_test_dna.dat");
StringCharFeatures charfeat = new StringCharFeatures(fm_train_dna, EAlphabet.DNA);
StringWordFeatures feats_train = new StringWordFeatures(charfeat.get_alphabet());
feats_train.obtain_from_char(charfeat, order - 1, order, gap, false);
charfeat = new StringCharFeatures(fm_test_dna, EAlphabet.DNA);
StringWordFeatures feats_test = new StringWordFeatures(charfeat.get_alphabet());
feats_test.obtain_from_char(charfeat, order - 1, order, gap, false);
PolyMatchWordStringKernel kernel = new PolyMatchWordStringKernel(feats_train, feats_train, degree, true);
double[,] km_train = kernel.get_kernel_matrix();
kernel.init(feats_train, feats_test);
double[,] km_test = kernel.get_kernel_matrix();
modshogun.exit_shogun();
}
public LocalAlignmentStringKernel(StringCharFeatures l, StringCharFeatures r) : this(modshogunPINVOKE.new_LocalAlignmentStringKernel__SWIG_4(StringCharFeatures.getCPtr(l), StringCharFeatures.getCPtr(r)), true)
{
if (modshogunPINVOKE.SWIGPendingException.Pending)
{
throw modshogunPINVOKE.SWIGPendingException.Retrieve();
}
}
public static void Main()
{
modshogun.init_shogun_with_defaults();
bool reverse = false;
int order = 3;
int gap = 0;
int degree = 2;
string[] fm_train_dna = Load.load_dna("../data/fm_train_dna.dat");
string[] fm_test_dna = Load.load_dna("../data/fm_test_dna.dat");
StringCharFeatures charfeat = new StringCharFeatures(fm_train_dna, EAlphabet.DNA);
StringWordFeatures feats_train = new StringWordFeatures(charfeat.get_alphabet());
feats_train.obtain_from_char(charfeat, order-1, order, gap, false);
charfeat = new StringCharFeatures(fm_test_dna, EAlphabet.DNA);
StringWordFeatures feats_test = new StringWordFeatures(charfeat.get_alphabet());
feats_test.obtain_from_char(charfeat, order-1, order, gap, false);
PolyMatchWordStringKernel kernel = new PolyMatchWordStringKernel(feats_train, feats_train, degree, true);
double[,] km_train = kernel.get_kernel_matrix();
kernel.init(feats_train, feats_test);
double[,] km_test=kernel.get_kernel_matrix();
}
public GaussianMatchStringKernel(StringCharFeatures l, StringCharFeatures r, double width) : this(modshogunPINVOKE.new_GaussianMatchStringKernel__SWIG_2(StringCharFeatures.getCPtr(l), StringCharFeatures.getCPtr(r), width), true)
{
if (modshogunPINVOKE.SWIGPendingException.Pending)
{
throw modshogunPINVOKE.SWIGPendingException.Retrieve();
}
}
public static void Main()
{
modshogun.init_shogun_with_defaults();
bool reverse = false;
int order = 3;
int gap = 0;
string[] fm_train_dna = Load.load_dna("../data/fm_train_dna.dat");
string[] fm_test_dna = Load.load_dna("../data/fm_test_dna.dat");
StringCharFeatures charfeat = new StringCharFeatures(fm_train_dna, EAlphabet.DNA);
StringWordFeatures feats_train = new StringWordFeatures(charfeat.get_alphabet());
feats_train.obtain_from_char(charfeat, order - 1, order, gap, reverse);
charfeat = new StringCharFeatures(fm_test_dna, EAlphabet.DNA);
StringWordFeatures feats_test = new StringWordFeatures(charfeat.get_alphabet());
feats_test.obtain_from_char(charfeat, order - 1, order, gap, reverse);
SortWordString preproc = new SortWordString();
preproc.init(feats_train);
feats_train.add_preprocessor(preproc);
feats_train.apply_preprocessor();
feats_test.add_preprocessor(preproc);
feats_test.apply_preprocessor();
CommWordStringKernel kernel = new CommWordStringKernel(feats_train, feats_train, false);
double[,] km_train = kernel.get_kernel_matrix();
kernel.init(feats_train, feats_test);
double[,] km_test = kernel.get_kernel_matrix();
}
internal static ArrayList run(IList para)
{
modshogun.init_shogun_with_defaults();
int degree = (int)((int?)para[0]);
string[] fm_train_dna = Load.load_dna("../data/fm_train_dna.dat");
string[] fm_test_dna = Load.load_dna("../data/fm_test_dna.dat");
StringCharFeatures feats_train = new StringCharFeatures(fm_train_dna, DNA);
StringCharFeatures feats_test = new StringCharFeatures(fm_test_dna, DNA);
WeightedDegreeStringKernel kernel = new WeightedDegreeStringKernel(feats_train, feats_train, degree);
double[] w = new double[degree];
double sum = degree * (degree + 1)/2;
for (int i = 0; i < degree; i++)
{
w[i] = (degree - i)/sum;
}
DoubleMatrix weights = new DoubleMatrix(1, degree, w);
kernel.set_wd_weights(weights);
DoubleMatrix km_train = kernel.get_kernel_matrix();
kernel.init(feats_train, feats_test);
DoubleMatrix km_test = kernel.get_kernel_matrix();
ArrayList result = new ArrayList();
result.Add(km_train);
result.Add(km_test);
result.Add(kernel);
modshogun.exit_shogun();
return result;
}
internal static ArrayList run(IList para)
{
int degree = 20;
modshogun.init_shogun_with_defaults();
double C = (double)((double?)para[0]);
double epsilon = (double)((double?)para[1]);
int num_threads = (int)((int?)para[2]);
string[] fm_train_dna = Load.load_dna("../data/fm_train_dna.dat");
string[] fm_test_dna = Load.load_dna("../data/fm_test_dna.dat");
StringCharFeatures feats_train = new StringCharFeatures(fm_train_dna, DNA);
StringCharFeatures feats_test = new StringCharFeatures(fm_test_dna, DNA);
Labels labels = new Labels(Load.load_labels("../data/label_train_dna.dat"));
WeightedDegreeStringKernel kernel = new WeightedDegreeStringKernel(feats_train, feats_train, degree);
SVMLight svm = new SVMLight(C, kernel, labels);
svm.set_epsilon(epsilon);
//svm.parallel.set_num_threads(num_threads);
svm.train();
kernel.init(feats_train, feats_test);
svm.apply().get_labels();
ArrayList result = new ArrayList();
result.Add(kernel);
modshogun.exit_shogun();
return result;
}
public static void Main() {
modshogun.init_shogun_with_defaults();
int order = 3;
int gap = 0;
bool reverse = false;
bool use_sign = false;
String[] fm_train_dna = Load.load_dna("../data/fm_train_dna.dat");
String[] fm_test_dna = Load.load_dna("../data/fm_test_dna.dat");
double[] fm_test_real = Load.load_labels("../data/fm_test_real.dat");
StringCharFeatures charfeat = new StringCharFeatures(EAlphabet.DNA);
charfeat.set_features(fm_train_dna);
StringWordFeatures feats_train = new StringWordFeatures(charfeat.get_alphabet());
feats_train.obtain_from_char(charfeat, order-1, order, gap, reverse);
SortWordString preproc = new SortWordString();
preproc.init(feats_train);
feats_train.add_preprocessor(preproc);
feats_train.apply_preprocessor();
StringCharFeatures charfeat_test = new StringCharFeatures(EAlphabet.DNA);
charfeat_test.set_features(fm_test_dna);
StringWordFeatures feats_test = new StringWordFeatures(charfeat.get_alphabet());
feats_test.obtain_from_char(charfeat_test, order-1, order, gap, reverse);
feats_test.add_preprocessor(preproc);
feats_test.apply_preprocessor();
HammingWordDistance distance = new HammingWordDistance(feats_train, feats_train, use_sign);
double[,] dm_train = distance.get_distance_matrix();
distance.init(feats_train, feats_test);
double[,] dm_test = distance.get_distance_matrix();
}
internal static ArrayList run(IList para)
{
bool reverse = false;
modshogun.init_shogun_with_defaults();
int order = (int)((int?)para[0]);
int gap = (int)((int?)para[1]);
int degree = (int)((int?)para[2]);
string[] fm_train_dna = Load.load_dna("../data/fm_train_dna.dat");
string[] fm_test_dna = Load.load_dna("../data/fm_test_dna.dat");
StringCharFeatures charfeat = new StringCharFeatures(fm_train_dna, DNA);
StringWordFeatures feats_train = new StringWordFeatures(charfeat.get_alphabet());
feats_train.obtain_from_char(charfeat, order-1, order, gap, false);
charfeat = new StringCharFeatures(fm_test_dna, DNA);
StringWordFeatures feats_test = new StringWordFeatures(charfeat.get_alphabet());
feats_test.obtain_from_char(charfeat, order-1, order, gap, false);
PolyMatchWordStringKernel kernel = new PolyMatchWordStringKernel(feats_train, feats_train, degree, true);
DoubleMatrix km_train = kernel.get_kernel_matrix();
kernel.init(feats_train, feats_test);
DoubleMatrix km_test =kernel.get_kernel_matrix();
ArrayList result = new ArrayList();
result.Add(km_train);
result.Add(km_test);
result.Add(kernel);
modshogun.exit_shogun();
return result;
}
static void Main(string[] argv)
{
modshogun.init_shogun_with_defaults();
int order = 3;
int gap = 0;
bool reverse = false;
string[] fm_train_dna = Load.load_dna("../data/fm_train_dna.dat");
string[] fm_test_dna = Load.load_dna("../data/fm_test_dna.dat");
DoubleMatrix fm_test_real = Load.load_numbers("../data/fm_test_real.dat");
StringCharFeatures charfeat = new StringCharFeatures(DNA);
charfeat.set_features(fm_train_dna);
StringWordFeatures feats_train = new StringWordFeatures(charfeat.get_alphabet());
feats_train.obtain_from_char(charfeat, order-1, order, gap, reverse);
SortWordString preproc = new SortWordString();
preproc.init(feats_train);
feats_train.add_preprocessor(preproc);
feats_train.apply_preprocessor();
StringCharFeatures charfeat_test = new StringCharFeatures(DNA);
charfeat_test.set_features(fm_test_dna);
StringWordFeatures feats_test = new StringWordFeatures(charfeat.get_alphabet());
feats_test.obtain_from_char(charfeat_test, order-1, order, gap, reverse);
feats_test.add_preprocessor(preproc);
feats_test.apply_preprocessor();
ManhattanWordDistance distance = new ManhattanWordDistance(feats_train, feats_train);
DoubleMatrix dm_train = distance.get_distance_matrix();
distance.init(feats_train, feats_test);
DoubleMatrix dm_test = distance.get_distance_matrix();
modshogun.exit_shogun();
}
public SpectrumMismatchRBFKernel(StringCharFeatures l, StringCharFeatures r, int size, SWIGTYPE_p_double AA_matrix_, int nr_, int nc_, int degree, int max_mismatch, double width) : this(modshogunPINVOKE.new_SpectrumMismatchRBFKernel__SWIG_2(StringCharFeatures.getCPtr(l), StringCharFeatures.getCPtr(r), size, SWIGTYPE_p_double.getCPtr(AA_matrix_), nr_, nc_, degree, max_mismatch, width), true)
{
if (modshogunPINVOKE.SWIGPendingException.Pending)
{
throw modshogunPINVOKE.SWIGPendingException.Retrieve();
}
}
public SimpleLocalityImprovedStringKernel(StringCharFeatures l, StringCharFeatures r, int length, int inner_degree, int outer_degree) : this(modshogunPINVOKE.new_SimpleLocalityImprovedStringKernel__SWIG_2(StringCharFeatures.getCPtr(l), StringCharFeatures.getCPtr(r), length, inner_degree, outer_degree), true)
{
if (modshogunPINVOKE.SWIGPendingException.Pending)
{
throw modshogunPINVOKE.SWIGPendingException.Retrieve();
}
}
public static void Main()
{
bool reverse = false;
modshogun.init_shogun_with_defaults();
int order = 3;
int gap = 4;
String[] fm_train_dna = Load.load_dna("../data/fm_train_dna.dat");
StringCharFeatures charfeat = new StringCharFeatures(fm_train_dna, EAlphabet.DNA);
StringWordFeatures feats = new StringWordFeatures(charfeat.get_alphabet());
feats.obtain_from_char(charfeat, order - 1, order, gap, reverse);
Histogram histo = new Histogram(feats);
histo.train();
double[] histogram = histo.get_histogram();
foreach (double item in histogram)
{
Console.Write(item);
}
//int num_examples = feats.get_num_vectors();
//int num_param = histo.get_num_model_parameters();
//double[,] out_likelihood = histo.get_log_likelihood();
//double out_sample = histo.get_log_likelihood_sample();
modshogun.exit_shogun();
}
internal static ArrayList run(IList para)
{
bool reverse = false;
modshogun.init_shogun_with_defaults();
int order = (int)((int?)para[0]);
int gap = (int)((int?)para[1]);
string[] fm_train_dna = Load.load_dna("../data/fm_train_dna.dat");
StringCharFeatures charfeat = new StringCharFeatures(fm_train_dna, DNA);
StringWordFeatures feats = new StringWordFeatures(charfeat.get_alphabet());
feats.obtain_from_char(charfeat, order-1, order, gap, reverse);
Histogram histo = new Histogram(feats);
histo.train();
histo.get_histogram();
int num_examples = feats.get_num_vectors();
int num_param = histo.get_num_model_parameters();
DoubleMatrix out_likelihood = histo.get_log_likelihood();
double out_sample = histo.get_log_likelihood_sample();
ArrayList result = new ArrayList();
result.Add(histo);
result.Add(out_sample);
result.Add(out_likelihood);
modshogun.exit_shogun();
return result;
}
static void Main(string[] argv)
{
modshogun.init_shogun_with_defaults();
int degree = 20;
double scale = 1.4;
int size_cache = 10;
int order = 3;
int gap = 0;
bool reverse = false;
string[] fm_train_dna = Load.load_dna("../data/fm_train_dna.dat");
string[] fm_test_dna = Load.load_dna("../data/fm_test_dna.dat");
StringCharFeatures charfeat = new StringCharFeatures(fm_train_dna, DNA);
StringWordFeatures feats_train = new StringWordFeatures(DNA);
feats_train.obtain_from_char(charfeat, order-1, order, gap, reverse);
StringCharFeatures charfeat_test = new StringCharFeatures(fm_test_dna, DNA);
StringWordFeatures feats_test = new StringWordFeatures(DNA);
feats_test.obtain_from_char(charfeat_test, order-1, order, gap, reverse);
MatchWordStringKernel kernel = new MatchWordStringKernel(size_cache, degree);
kernel.set_normalizer(new AvgDiagKernelNormalizer(scale));
kernel.init(feats_train, feats_train);
DoubleMatrix km_train = kernel.get_kernel_matrix();
kernel.init(feats_train, feats_test);
DoubleMatrix km_test = kernel.get_kernel_matrix();
modshogun.exit_shogun();
}
public static void Main() {
bool reverse = false;
modshogun.init_shogun_with_defaults();
int order = 3;
int gap = 4;
String[] fm_train_dna = Load.load_dna("../data/fm_train_dna.dat");
StringCharFeatures charfeat = new StringCharFeatures(fm_train_dna, EAlphabet.DNA);
StringWordFeatures feats = new StringWordFeatures(charfeat.get_alphabet());
feats.obtain_from_char(charfeat, order-1, order, gap, reverse);
Histogram histo = new Histogram(feats);
histo.train();
double[] histogram = histo.get_histogram();
foreach(double item in histogram) {
Console.Write(item);
}
//int num_examples = feats.get_num_vectors();
//int num_param = histo.get_num_model_parameters();
//double[,] out_likelihood = histo.get_log_likelihood();
//double out_sample = histo.get_log_likelihood_sample();
modshogun.exit_shogun();
}
public DistantSegmentsKernel(StringCharFeatures l, StringCharFeatures r, int size, int delta, int theta) : this(modshogunPINVOKE.new_DistantSegmentsKernel__SWIG_2(StringCharFeatures.getCPtr(l), StringCharFeatures.getCPtr(r), size, delta, theta), true)
{
if (modshogunPINVOKE.SWIGPendingException.Pending)
{
throw modshogunPINVOKE.SWIGPendingException.Retrieve();
}
}
public SNPStringKernel(StringCharFeatures l, StringCharFeatures r, int degree, int win_len, bool inhomogene) : this(modshogunPINVOKE.new_SNPStringKernel__SWIG_2(StringCharFeatures.getCPtr(l), StringCharFeatures.getCPtr(r), degree, win_len, inhomogene), true)
{
if (modshogunPINVOKE.SWIGPendingException.Pending)
{
throw modshogunPINVOKE.SWIGPendingException.Retrieve();
}
}
internal static ArrayList run(IList para)
{
modshogun.init_shogun_with_defaults();
int degree = (int)((int?)para[0]);
string[] fm_train_dna = Load.load_dna("../data/fm_train_dna.dat");
string[] fm_test_dna = Load.load_dna("../data/fm_test_dna.dat");
StringCharFeatures feats_train = new StringCharFeatures(fm_train_dna, DNA);
StringCharFeatures feats_test = new StringCharFeatures(fm_test_dna, DNA);
WeightedDegreePositionStringKernel kernel = new WeightedDegreePositionStringKernel(feats_train, feats_train, degree);
kernel.set_position_weights(DoubleMatrix.ones(1, (fm_train_dna[0]).Length));
DoubleMatrix km_train = kernel.get_kernel_matrix();
kernel.init(feats_train, feats_test);
DoubleMatrix km_test = kernel.get_kernel_matrix();
ArrayList result = new ArrayList();
result.Add(km_train);
result.Add(km_test);
result.Add(kernel);
modshogun.exit_shogun();
return result;
}
public virtual bool Align_char_features(StringCharFeatures cf, StringCharFeatures Ref, double gapCost)
{
bool ret = modshogunPINVOKE.WordFeatures_Align_char_features(swigCPtr, StringCharFeatures.getCPtr(cf), StringCharFeatures.getCPtr(Ref), gapCost);
if (modshogunPINVOKE.SWIGPendingException.Pending)
{
throw modshogunPINVOKE.SWIGPendingException.Retrieve();
}
return(ret);
}
public bool append_features(StringCharFeatures sf)
{
bool ret = modshogunPINVOKE.StringCharFeatures_append_features(swigCPtr, StringCharFeatures.getCPtr(sf));
if (modshogunPINVOKE.SWIGPendingException.Pending)
{
throw modshogunPINVOKE.SWIGPendingException.Retrieve();
}
return(ret);
}
public bool obtain_from_char(StringCharFeatures sf, int start, int p_order, int gap, bool rev)
{
bool ret = modshogunPINVOKE.StringShortRealFeatures_obtain_from_char(swigCPtr, StringCharFeatures.getCPtr(sf), start, p_order, gap, rev);
if (modshogunPINVOKE.SWIGPendingException.Pending)
{
throw modshogunPINVOKE.SWIGPendingException.Retrieve();
}
return(ret);
}
public static void Main() {
modshogun.init_shogun_with_defaults();
string [] strings = new string[6] { "hey","guys","i","am","a","string"};
StringCharFeatures f = new StringCharFeatures(strings, EAlphabet.RAWBYTE);
string [] r = f.get_features();
foreach(string item in r) {
Console.WriteLine(item);
}
}
public StringCharFeatures get_transposed()
{
IntPtr cPtr = modshogunPINVOKE.StringCharFeatures_get_transposed(swigCPtr);
StringCharFeatures ret = (cPtr == IntPtr.Zero) ? null : new StringCharFeatures(cPtr, true);
if (modshogunPINVOKE.SWIGPendingException.Pending)
{
throw modshogunPINVOKE.SWIGPendingException.Retrieve();
}
return(ret);
}
internal static ArrayList run(string[] strs)
{
modshogun.init_shogun_with_defaults();
StringCharFeatures f = new StringCharFeatures(strings, RAWBYTE);
f.set_feature_vector(new DoubleMatrix(new double[][] {{'t','e','s','t'}}), 0);
ArrayList result = new ArrayList();
result.Add(f.get_features());
result.Add(f);
modshogun.exit_shogun();
return result;
}
public static void Main()
{
bool reverse = false;
modshogun.init_shogun_with_defaults();
int N = 1;
int M = 512;
double pseudo = 1e-5;
int order = 3;
int gap = 0;
string[] fm_train_dna = Load.load_cubes("../data/fm_train_cube.dat");
StringCharFeatures charfeat = new StringCharFeatures(fm_train_dna, EAlphabet.CUBE);
StringWordFeatures feats = new StringWordFeatures(charfeat.get_alphabet());
feats.obtain_from_char(charfeat, order - 1, order, gap, reverse);
HMM hmm = new HMM(feats, N, M, pseudo);
hmm.train();
hmm.baum_welch_viterbi_train(BaumWelchViterbiType.BW_NORMAL);
int num_examples = feats.get_num_vectors();
int num_param = hmm.get_num_model_parameters();
for (int i = 0; i < num_examples; i++)
{
for (int j = 0; j < num_param; j++)
{
hmm.get_log_derivative(j, i);
}
}
int best_path = 0;
int best_path_state = 0;
for (int i = 0; i < num_examples; i++)
{
best_path += (int)hmm.best_path(i);
for (int j = 0; j < N; j++)
{
best_path_state += hmm.get_best_path_state(i, j);
}
}
double[] lik_example = hmm.get_log_likelihood();
double lik_sample = hmm.get_log_likelihood_sample();
modshogun.exit_shogun();
}
internal static ArrayList run(IList para)
{
bool reverse = false;
modshogun.init_shogun_with_defaults();
int N = (int)((int?)para[0]);
int M = (int)((int?)para[1]);
double pseudo = (double)((double?)para[2]);
int order = (int)((int?)para[3]);
int gap = (int)((int?)para[4]);
string[] fm_train_dna = Load.load_cubes("../data/fm_train_cube.dat");
StringCharFeatures charfeat = new StringCharFeatures(fm_train_dna, CUBE);
StringWordFeatures feats = new StringWordFeatures(charfeat.get_alphabet());
feats.obtain_from_char(charfeat, order-1, order, gap, reverse);
HMM hmm = new HMM(feats, N, M, pseudo);
hmm.train();
hmm.baum_welch_viterbi_train(BW_NORMAL);
int num_examples = feats.get_num_vectors();
int num_param = hmm.get_num_model_parameters();
for (int i = 0; i < num_examples; i++)
{
for(int j = 0; j < num_param; j++)
{
hmm.get_log_derivative(j, i);
}
}
int best_path = 0;
int best_path_state = 0;
for(int i = 0; i < num_examples; i++)
{
best_path += hmm.best_path(i);
for(int j = 0; j < N; j++)
{
best_path_state += hmm.get_best_path_state(i, j);
}
}
DoubleMatrix lik_example = hmm.get_log_likelihood();
double lik_sample = hmm.get_log_likelihood_sample();
ArrayList result = new ArrayList();
result.Add(lik_example);
result.Add(lik_sample);
result.Add(hmm);
modshogun.exit_shogun();
return result;
}
public static void Main()
{
modshogun.init_shogun_with_defaults();
int cardinality = 2;
int cache = 10;
double[,] traindata_real = Load.load_numbers("../data/fm_train_real.dat");
double[,] testdata_real = Load.load_numbers("../data/fm_test_real.dat");
String[] fm_train_dna = Load.load_dna("../data/fm_train_dna.dat");
String[] fm_test_dna = Load.load_dna("../data/fm_test_dna.dat");
RealFeatures subfeats_train = new RealFeatures(traindata_real);
RealFeatures subfeats_test = new RealFeatures(testdata_real);
CombinedKernel kernel = new CombinedKernel();
CombinedFeatures feats_train = new CombinedFeatures();
CombinedFeatures feats_test = new CombinedFeatures();
GaussianKernel subkernel = new GaussianKernel(cache, 1.1);
feats_train.append_feature_obj(subfeats_train);
feats_test.append_feature_obj(subfeats_test);
kernel.append_kernel(subkernel);
StringCharFeatures subkfeats_train = new StringCharFeatures(fm_train_dna, EAlphabet.DNA);
StringCharFeatures subkfeats_test = new StringCharFeatures(fm_test_dna, EAlphabet.DNA);
int degree = 3;
FixedDegreeStringKernel subkernel2 = new FixedDegreeStringKernel(10, degree);
feats_train.append_feature_obj(subkfeats_train);
feats_test.append_feature_obj(subkfeats_test);
kernel.append_kernel(subkernel2);
subkfeats_train = new StringCharFeatures(fm_train_dna, EAlphabet.DNA);
subkfeats_test = new StringCharFeatures(fm_test_dna, EAlphabet.DNA);
LocalAlignmentStringKernel subkernel3 = new LocalAlignmentStringKernel(10);
feats_train.append_feature_obj(subkfeats_train);
feats_test.append_feature_obj(subkfeats_test);
kernel.append_kernel(subkernel3);
kernel.init(feats_train, feats_train);
double[,] km_train = kernel.get_kernel_matrix();
kernel.init(feats_train, feats_test);
double[,] km_test = kernel.get_kernel_matrix();
modshogun.exit_shogun();
}
public virtual object run(IList para)
{
modshogun.init_shogun_with_defaults();
int cardinality = (int)((int?)para[0]);
int size_cache = (int)((int?)para[1]);
DoubleMatrix traindata_real = Load.load_numbers("../data/fm_train_real.dat");
DoubleMatrix testdata_real = Load.load_numbers("../data/fm_test_real.dat");
string[] fm_train_dna = Load.load_dna("../data/fm_train_dna.dat");
string[] fm_test_dna = Load.load_dna("../data/fm_test_dna.dat");
RealFeatures subfeats_train = new RealFeatures(traindata_real);
RealFeatures subfeats_test = new RealFeatures(testdata_real);
CombinedKernel kernel = new CombinedKernel();
CombinedFeatures feats_train = new CombinedFeatures();
CombinedFeatures feats_test = new CombinedFeatures();
GaussianKernel subkernel = new GaussianKernel(10, 1.1);
feats_train.append_feature_obj(subfeats_train);
feats_test.append_feature_obj(subfeats_test);
kernel.append_kernel(subkernel);
StringCharFeatures subkfeats_train = new StringCharFeatures(fm_train_dna, DNA);
StringCharFeatures subkfeats_test = new StringCharFeatures(fm_test_dna, DNA);
int degree = 3;
FixedDegreeStringKernel subkernel2 = new FixedDegreeStringKernel(10, degree);
feats_train.append_feature_obj(subkfeats_train);
feats_test.append_feature_obj(subkfeats_test);
kernel.append_kernel(subkernel2);
subkfeats_train = new StringCharFeatures(fm_train_dna, DNA);
subkfeats_test = new StringCharFeatures(fm_test_dna, DNA);
LocalAlignmentStringKernel subkernel3 = new LocalAlignmentStringKernel(10);
feats_train.append_feature_obj(subkfeats_train);
feats_test.append_feature_obj(subkfeats_test);
kernel.append_kernel(subkernel3);
kernel.init(feats_train, feats_train);
DoubleMatrix km_train =kernel.get_kernel_matrix();
kernel.init(feats_train, feats_test);
DoubleMatrix km_test =kernel.get_kernel_matrix();
ArrayList result = new ArrayList();
result.Add(km_train);
result.Add(km_test);
result.Add(kernel);
modshogun.exit_shogun();
return (object)result;
}
public static void Main()
{
modshogun.init_shogun_with_defaults();
string [] strings = new string[6] {
"hey", "guys", "i", "am", "a", "string"
};
StringCharFeatures f = new StringCharFeatures(strings, EAlphabet.RAWBYTE);
string [] r = f.get_features();
foreach (string item in r)
{
Console.WriteLine(item);
}
}
public static void Main()
{
modshogun.init_shogun_with_defaults();
int order = 3;
int gap = 0;
bool reverse = false;
String[] fm_train_dna = Load.load_dna("../data/fm_train_dna.dat");
String[] fm_test_dna = Load.load_dna("../data/fm_test_dna.dat");
double[,] fm_test_real = Load.load_numbers("../data/fm_test_real.dat");
StringCharFeatures charfeat = new StringCharFeatures(EAlphabet.DNA);
charfeat.set_features(fm_train_dna);
StringWordFeatures feats_train = new StringWordFeatures(charfeat.get_alphabet());
feats_train.obtain_from_char(charfeat, order - 1, order, gap, reverse);
SortWordString preproc = new SortWordString();
preproc.init(feats_train);
feats_train.add_preprocessor(preproc);
feats_train.apply_preprocessor();
StringCharFeatures charfeat_test = new StringCharFeatures(EAlphabet.DNA);
charfeat_test.set_features(fm_test_dna);
StringWordFeatures feats_test = new StringWordFeatures(charfeat.get_alphabet());
feats_test.obtain_from_char(charfeat_test, order - 1, order, gap, reverse);
feats_test.add_preprocessor(preproc);
feats_test.apply_preprocessor();
ManhattanWordDistance distance = new ManhattanWordDistance(feats_train, feats_train);
double[,] dm_train = distance.get_distance_matrix();
distance.init(feats_train, feats_test);
double[,] dm_test = distance.get_distance_matrix();
foreach (double item in dm_train)
{
Console.Write(item);
}
foreach (double item in dm_test)
{
Console.Write(item);
}
modshogun.exit_shogun();
}
internal static ArrayList run(string[] strs)
{
modshogun.init_shogun_with_defaults();
StringCharFeatures cf = new StringCharFeatures(strings, RAWBYTE);
StringWordFeatures wf = new StringWordFeatures(RAWBYTE);
wf.obtain_from_char(cf, 0, 2, 0, false);
wf.set_feature_vector(new DoubleMatrix(new double[][] {{1,2,3,4,5}}), 0);
ArrayList result = new ArrayList();
//result.add(wf.get_features());
result.Add(wf);
modshogun.exit_shogun();
return result;
}
public static void Main() {
modshogun.init_shogun_with_defaults();
String[] strings = new String[] {"AAAAAAAAAACCCCCCCCCCGGGGGGGGGGTTTTTTTTTT"};
StringCharFeatures f = new StringCharFeatures(strings, EAlphabet.DNA);
f.obtain_by_sliding_window(5,1);
DynamicIntArray positions = new DynamicIntArray();
positions.append_element(0);
positions.append_element(6);
positions.append_element(16);
positions.append_element(25);
//f.obtain_by_position_list(8,positions);
}
public static void Main()
{
modshogun.init_shogun_with_defaults();
int cardinality = 2;
int cache = 10;
double[,] traindata_real = Load.load_numbers("../data/fm_train_real.dat");
double[,] testdata_real = Load.load_numbers("../data/fm_test_real.dat");
String[] fm_train_dna = Load.load_dna("../data/fm_train_dna.dat");
String[] fm_test_dna = Load.load_dna("../data/fm_test_dna.dat");
RealFeatures subfeats_train = new RealFeatures(traindata_real);
RealFeatures subfeats_test = new RealFeatures(testdata_real);
CombinedKernel kernel= new CombinedKernel();
CombinedFeatures feats_train = new CombinedFeatures();
CombinedFeatures feats_test = new CombinedFeatures();
GaussianKernel subkernel = new GaussianKernel(cache, 1.1);
feats_train.append_feature_obj(subfeats_train);
feats_test.append_feature_obj(subfeats_test);
kernel.append_kernel(subkernel);
StringCharFeatures subkfeats_train = new StringCharFeatures(fm_train_dna, EAlphabet.DNA);
StringCharFeatures subkfeats_test = new StringCharFeatures(fm_test_dna, EAlphabet.DNA);
int degree = 3;
FixedDegreeStringKernel subkernel2= new FixedDegreeStringKernel(10, degree);
feats_train.append_feature_obj(subkfeats_train);
feats_test.append_feature_obj(subkfeats_test);
kernel.append_kernel(subkernel2);
subkfeats_train = new StringCharFeatures(fm_train_dna, EAlphabet.DNA);
subkfeats_test = new StringCharFeatures(fm_test_dna, EAlphabet.DNA);
LocalAlignmentStringKernel subkernel3 = new LocalAlignmentStringKernel(10);
feats_train.append_feature_obj(subkfeats_train);
feats_test.append_feature_obj(subkfeats_test);
kernel.append_kernel(subkernel3);
kernel.init(feats_train, feats_train);
double[,] km_train=kernel.get_kernel_matrix();
kernel.init(feats_train, feats_test);
double[,] km_test=kernel.get_kernel_matrix();
modshogun.exit_shogun();
}
public static void Main()
{
modshogun.init_shogun_with_defaults();
String[] fm_train_dna = Load.load_dna("../data/fm_train_dna.dat");
String[] fm_test_dna = Load.load_dna("../data/fm_test_dna.dat");
StringCharFeatures feats_train = new StringCharFeatures(fm_train_dna, EAlphabet.DNA);
StringCharFeatures feats_test = new StringCharFeatures(fm_test_dna, EAlphabet.DNA);
LocalAlignmentStringKernel kernel = new LocalAlignmentStringKernel(feats_train, feats_train);
double[,] km_train = kernel.get_kernel_matrix();
kernel.init(feats_train, feats_test);
double[,] km_test = kernel.get_kernel_matrix();
}
internal static ArrayList run(string filename)
{
modshogun.init_shogun_with_defaults();
StringCharFeatures f = new StringCharFeatures(RAWBYTE);
f.load_from_directory(".");
AsciiFile fil = new AsciiFile(fname);
f.load(fil);
ArrayList result = new ArrayList();
result.Add(f.get_features());
result.Add(f);
modshogun.exit_shogun();
return result;
}
public static void Main() {
modshogun.init_shogun_with_defaults();
String[] fm_train_dna = Load.load_dna("../data/fm_train_dna.dat");
String[] fm_test_dna = Load.load_dna("../data/fm_test_dna.dat");
StringCharFeatures feats_train = new StringCharFeatures(fm_train_dna, EAlphabet.DNA);
StringCharFeatures feats_test = new StringCharFeatures(fm_test_dna, EAlphabet.DNA);
LocalAlignmentStringKernel kernel = new LocalAlignmentStringKernel(feats_train, feats_train);
double[,] km_train = kernel.get_kernel_matrix();
kernel.init(feats_train, feats_test);
double[,] km_test = kernel.get_kernel_matrix();
modshogun.exit_shogun();
}
public static void Main()
{
modshogun.init_shogun_with_defaults();
bool reverse = false;
int degree = 3;
String[] fm_train_dna = Load.load_dna("../data/fm_train_dna.dat");
String[] fm_test_dna = Load.load_dna("../data/fm_test_dna.dat");
StringCharFeatures feats_train = new StringCharFeatures(fm_train_dna, EAlphabet.DNA);
StringCharFeatures feats_test = new StringCharFeatures(fm_test_dna, EAlphabet.DNA);
PolyMatchStringKernel kernel = new PolyMatchStringKernel(feats_train, feats_train, degree, true);
double[,] km_train = kernel.get_kernel_matrix();
kernel.init(feats_train, feats_test);
double[,] km_test=kernel.get_kernel_matrix();
}
static void Main(string[] argv)
{
modshogun.init_shogun_with_defaults();
string[] fm_train_dna = Load.load_dna("../data/fm_train_dna.dat");
string[] fm_test_dna = Load.load_dna("../data/fm_test_dna.dat");
StringCharFeatures feats_train = new StringCharFeatures(fm_train_dna, DNA);
StringCharFeatures feats_test = new StringCharFeatures(fm_test_dna, DNA);
LinearStringKernel kernel = new LinearStringKernel(feats_train, feats_train);
DoubleMatrix km_train = kernel.get_kernel_matrix();
kernel.init(feats_train, feats_test);
DoubleMatrix km_test = kernel.get_kernel_matrix();
modshogun.exit_shogun();
}
public static void Main()
{
modshogun.init_shogun_with_defaults();
int degree = 20;
String[] fm_train_dna = Load.load_dna("../data/fm_train_dna.dat");
String[] fm_test_dna = Load.load_dna("../data/fm_test_dna.dat");
StringCharFeatures feats_train = new StringCharFeatures(fm_train_dna, EAlphabet.DNA);
StringCharFeatures feats_test = new StringCharFeatures(fm_test_dna, EAlphabet.DNA);
WeightedDegreePositionStringKernel kernel = new WeightedDegreePositionStringKernel(feats_train, feats_train, degree);
double[,] km_train = kernel.get_kernel_matrix();
kernel.init(feats_train, feats_test);
double[,] km_test = kernel.get_kernel_matrix();
}
public static void Main()
{
modshogun.init_shogun_with_defaults();
int degree = 20;
String[] fm_train_dna = Load.load_dna("../data/fm_train_dna.dat");
String[] fm_test_dna = Load.load_dna("../data/fm_test_dna.dat");
StringCharFeatures feats_train = new StringCharFeatures(fm_train_dna, EAlphabet.DNA);
StringCharFeatures feats_test = new StringCharFeatures(fm_test_dna, EAlphabet.DNA);
WeightedDegreePositionStringKernel kernel = new WeightedDegreePositionStringKernel(feats_train, feats_train, degree);
double[,] km_train = kernel.get_kernel_matrix();
kernel.init(feats_train, feats_test);
double[,] km_test = kernel.get_kernel_matrix();
}
public static void Main()
{
modshogun.init_shogun_with_defaults();
bool reverse = false;
int degree = 3;
String[] fm_train_dna = Load.load_dna("../data/fm_train_dna.dat");
String[] fm_test_dna = Load.load_dna("../data/fm_test_dna.dat");
StringCharFeatures feats_train = new StringCharFeatures(fm_train_dna, EAlphabet.DNA);
StringCharFeatures feats_test = new StringCharFeatures(fm_test_dna, EAlphabet.DNA);
PolyMatchStringKernel kernel = new PolyMatchStringKernel(feats_train, feats_train, degree, true);
double[,] km_train = kernel.get_kernel_matrix();
kernel.init(feats_train, feats_test);
double[,] km_test = kernel.get_kernel_matrix();
}
static void Main(string[] argv)
{
modshogun.init_shogun_with_defaults();
int degree = 20;
string[] fm_train_dna = Load.load_dna("../data/fm_train_dna.dat");
string[] fm_test_dna = Load.load_dna("../data/fm_test_dna.dat");
StringCharFeatures feats_train = new StringCharFeatures(fm_train_dna, DNA);
StringCharFeatures feats_test = new StringCharFeatures(fm_test_dna, DNA);
WeightedDegreePositionStringKernel kernel = new WeightedDegreePositionStringKernel(feats_train, feats_train, degree);
DoubleMatrix km_train = kernel.get_kernel_matrix();
kernel.init(feats_train, feats_test);
DoubleMatrix km_test = kernel.get_kernel_matrix();
modshogun.exit_shogun();
}
public static void Main()
{
modshogun.init_shogun_with_defaults();
int degree = 3;
string[] fm_train_dna = Load.load_dna("../data/fm_train_dna.dat");
string[] fm_test_dna = Load.load_dna("../data/fm_test_dna.dat");
foreach (string item in fm_train_dna)
{
Console.WriteLine(item);
}
StringCharFeatures feats_train = new StringCharFeatures(fm_train_dna, EAlphabet.DNA);
StringCharFeatures feats_test = new StringCharFeatures(fm_test_dna, EAlphabet.DNA);
WeightedDegreeStringKernel kernel = new WeightedDegreeStringKernel(feats_train, feats_train, degree);
double [] w = new double[degree];
double sum = degree * (degree + 1) / 2;
for (int i = 0; i < degree; i++)
{
w[i] = (degree - i) / sum;
}
kernel.set_wd_weights(w);
double[,] km_train = kernel.get_kernel_matrix();
kernel.init(feats_train, feats_test);
double[,] km_test = kernel.get_kernel_matrix();
foreach (double item in km_train)
{
Console.Write(item);
}
foreach (double item in km_test)
{
Console.Write(item);
}
modshogun.exit_shogun();
}
public static void Main()
{
modshogun.init_shogun_with_defaults();
int length = 5;
int inner_degree = 5;
int outer_degree = 7;
String[] fm_train_dna = Load.load_dna("../data/fm_train_dna.dat");
String[] fm_test_dna = Load.load_dna("../data/fm_test_dna.dat");
StringCharFeatures feats_train = new StringCharFeatures(fm_train_dna, EAlphabet.DNA);
StringCharFeatures feats_test = new StringCharFeatures(fm_test_dna, EAlphabet.DNA);
LocalityImprovedStringKernel kernel = new LocalityImprovedStringKernel(feats_train, feats_train, length, inner_degree, outer_degree);
double[,] km_train = kernel.get_kernel_matrix();
kernel.init(feats_train, feats_test);
double[,] km_test = kernel.get_kernel_matrix();
}
