/dports/math/mlpack/mlpack-3.4.2/src/mlpack/methods/hmm/ |
H A D | hmm_regression_impl.hpp | 27 StackData(predictors, responses, dataSeq); in Train() 36 StackData(predictors, responses, dataSeq); in Train() 52 StackData(predictors, responses, dataSeq); in Estimate() 66 StackData(predictors, responses, dataSeq); in Estimate() 80 StackData(predictors, responses, dataSeq); in Predict() 91 StackData(predictors, responses, dataSeq); in LogLikelihood() 121 emission[i].Predict(predictors.cols(ahead, predictors.n_cols-1), nextSeq); in Filter() 157 StackData(predictors, responses, dataSeq); in Forward() 168 StackData(predictors, responses, dataSeq); in Backward() 179 nextSeq = predictors[i]; in StackData() [all …]
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H A D | hmm_regression.hpp | 157 void Train(const std::vector<arma::mat>& predictors, 178 void Train(const std::vector<arma::mat>& predictors, 201 double Estimate(const arma::mat& predictors, 220 double Estimate(const arma::mat& predictors, 235 double Predict(const arma::mat& predictors, 246 double LogLikelihood(const arma::mat& predictors, 261 void Filter(const arma::mat& predictors, 278 void Smooth(const arma::mat& predictors, 290 void StackData(const arma::mat& predictors, 305 void Forward(const arma::mat& predictors, [all …]
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/dports/math/mlpack/mlpack-3.4.2/src/mlpack/tests/ |
H A D | augmented_rnns_tasks_test.cpp | 62 void Predict(arma::mat& predictors, in Predict() argument 78 size_t sz = predictors.n_elem; in Predict() 105 predictors = predictors.t(); in Predict() 106 predictors.reshape(bitLen, predictors.n_elem / bitLen); in Predict() 107 size_t len = predictors.n_cols; in Predict() 116 val += predictors.at(k, j); in Predict() 131 size_t sz = predictors.n_elem; in Predict() 159 predictors = predictors.t(); in Predict() 160 predictors.reshape(3, predictors.n_elem / 3); in Predict() 161 assert(predictors.n_rows == 3); in Predict() [all …]
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H A D | linear_regression_test.cpp | 28 arma::mat predictors(3, 10); variable 45 points = predictors; 52 predictors[elem] += math::Random() / 50.0; 61 LinearRegression lr(predictors, responses); 75 arma::mat predictors; variable 82 LinearRegression lr(predictors, responses); 94 arma::mat predictors; variable 138 arma::mat predictors(3, 10); variable 155 points = predictors; 231 arma::mat predictors(3, 10); variable [all …]
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/dports/math/ensmallen/ensmallen-2.17.0/include/ensmallen_bits/problems/ |
H A D | logistic_regression_function_impl.hpp | 23 MatType& predictors, in LogisticRegressionFunction() argument 27 predictors(predictors), in LogisticRegressionFunction() 48 MatType& predictors, in LogisticRegressionFunction() argument 53 predictors(predictors), in LogisticRegressionFunction() 74 predictors.n_cols - 1, predictors.n_cols)); in Shuffle() 76 newPredictors.set_size(predictors.n_rows, predictors.n_cols); in Shuffle() 82 predictors = std::move(newPredictors); in Shuffle() 180 predictors.t() + regularization; in Gradient() 198 / predictors.n_cols * batchSize; in Gradient() 267 predictors.t() + regularization; in EvaluateWithGradient() [all …]
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H A D | logistic_regression_function.hpp | 29 LogisticRegressionFunction(MatType& predictors, 33 LogisticRegressionFunction(MatType& predictors, 49 const MatType& Predictors() const { return predictors; } in Predictors() 157 size_t NumFunctions() const { return predictors.n_cols; } in NumFunctions() 160 size_t NumFeatures() const { return predictors.n_rows + 1; } in NumFeatures() 177 double ComputeAccuracy(const MatType& predictors, 204 MatType& predictors; member in ens::test::LogisticRegressionFunction
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/dports/devel/R-cran-caret/caret/man/ |
H A D | predictors.Rd | 3 \name{predictors} 4 \alias{predictors} 5 \alias{predictors.formula} 6 \alias{predictors.terms} 7 \alias{predictors.train} 8 \alias{predictors.default} 9 \alias{predictors.list} 10 \alias{predictors.rfe} 11 \alias{predictors.sbf} 14 predictors(x, ...) [all …]
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H A D | twoClassSim.Rd | 42 \item{noiseVars}{The number of uncorrelated irrelevant predictors to be 45 \item{corrVars}{The number of correlated irrelevant predictors to be 53 \item{factors}{Should the binary predictors be converted to factors?} 74 predictors (\code{J}, \code{K} and \code{L} above).} \item{Linear1, 75 }{Optional uncorrelated standard normal predictors (\code{C} through 80 normal predictors (each with unit variances)}\item{list()}{Optional 85 important predictors and irrelevant predictions. 100 predictors in this set, their contribution to the log-odds would be 110 systems and use two more predictors (\code{K} and \code{L}): 174 or a set number of predictors that follow a particular correlation [all …]
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/dports/math/mlpack/mlpack-3.4.2/src/mlpack/methods/linear_regression/ |
H A D | linear_regression.cpp | 19 LinearRegression::LinearRegression(const arma::mat& predictors, in LinearRegression() argument 26 LinearRegression::LinearRegression(const arma::mat& predictors, in LinearRegression() argument 34 Train(predictors, responses, weights, intercept); in LinearRegression() 37 double LinearRegression::Train(const arma::mat& predictors, in Train() argument 44 double LinearRegression::Train(const arma::mat& predictors, in Train() argument 60 const size_t nCols = predictors.n_cols; in Train() 62 arma::mat p = predictors; in Train() 88 return ComputeError(predictors, responses); in Train() 119 const size_t nCols = predictors.n_cols; in ComputeError() 120 const size_t nRows = predictors.n_rows; in ComputeError() [all …]
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/dports/math/mlpack/mlpack-3.4.2/src/mlpack/methods/logistic_regression/ |
H A D | logistic_regression_function_impl.hpp | 25 const MatType& predictors, in LogisticRegressionFunction() argument 29 predictors(math::MakeAlias(const_cast<MatType&>(predictors), false)), in LogisticRegressionFunction() 35 if (responses.n_elem != predictors.n_cols) in LogisticRegressionFunction() 56 math::ClearAlias(predictors); in Shuffle() 60 predictors = std::move(newPredictors); in Shuffle() 116 (batchSize / (2.0 * predictors.n_cols)) * in Evaluate() 151 predictors.t() + regularization; in Gradient() 167 / predictors.n_cols * batchSize; in Gradient() 171 predictors.cols(begin, begin + batchSize - 1); in Gradient() 230 predictors.t() + regularization; in EvaluateWithGradient() [all …]
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H A D | logistic_regression_impl.hpp | 25 const MatType& predictors, in LogisticRegression() argument 30 Train(predictors, responses); in LogisticRegression() 35 const MatType& predictors, in LogisticRegression() argument 42 Train(predictors, responses); in LogisticRegression() 58 const MatType& predictors, in LogisticRegression() argument 64 Train(predictors, responses, optimizer); in LogisticRegression() 70 const MatType& predictors, in Train() argument 81 const MatType& predictors, in Train() argument 90 if (parameters.n_elem != predictors.n_rows + 1) in Train() 142 const MatType& predictors, in ComputeError() argument [all …]
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H A D | logistic_regression.hpp | 57 LogisticRegression(const MatType& predictors, 77 LogisticRegression(const MatType& predictors, 111 LogisticRegression(const MatType& predictors, 134 double Train(const MatType& predictors, 157 double Train(const MatType& predictors, 225 double ComputeAccuracy(const MatType& predictors, 237 double ComputeError(const MatType& predictors,
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/dports/multimedia/xvid/xvidcore/src/prediction/ |
H A D | mbprediction.c | 69 int16_t predictors[8], in predict_acdc() 218 int16_t predictors[8], in add_acdc() 278 int16_t predictors[8]) in calc_acdc_coeff() 304 level -= predictors[i]; in calc_acdc_coeff() 306 predictors[i] = level; in calc_acdc_coeff() 315 level -= predictors[i]; in calc_acdc_coeff() 317 predictors[i] = level; in calc_acdc_coeff() 335 int16_t predictors[8]) in calc_acdc_bits() 363 predictors[i] = qcoeff[i]; in calc_acdc_bits() 393 int16_t predictors[8]) in apply_acdc() [all …]
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/dports/science/py-dlib/dlib-19.22/tools/python/test/ |
H A D | test_svm_c_trainer.py | 24 predictors = vectors() 31 predictors.append(vector(values)) 36 return predictors, sparse_predictors, response 54 predictors, sparse_predictors, response = training_data 56 predictors = sparse_predictors 57 cv = cross_validate_trainer(trainer(), predictors, response, folds=10) 61 decision_function = trainer().train(predictors, response) 62 assert decision_function(predictors[2]) < 0 63 assert decision_function(predictors[3]) > 0
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/dports/science/dlib-cpp/dlib-19.22/tools/python/test/ |
H A D | test_svm_c_trainer.py | 24 predictors = vectors() 31 predictors.append(vector(values)) 36 return predictors, sparse_predictors, response 54 predictors, sparse_predictors, response = training_data 56 predictors = sparse_predictors 57 cv = cross_validate_trainer(trainer(), predictors, response, folds=10) 61 decision_function = trainer().train(predictors, response) 62 assert decision_function(predictors[2]) < 0 63 assert decision_function(predictors[3]) > 0
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/dports/math/mlpack/mlpack-3.4.2/src/mlpack/methods/ann/ |
H A D | rnn_impl.hpp | 103 arma::cube predictors, in Train() argument 110 this->predictors = std::move(predictors); in Train() 148 arma::cube predictors, in Train() argument 154 this->predictors = std::move(predictors); in Train() 198 size_t(predictors.n_cols)); in Predict() 200 Forward(arma::mat(predictors.slice(0).colptr(0), predictors.n_rows, in Predict() 214 size_t(predictors.n_cols - begin)); in Predict() 248 inputSize = predictors.n_rows; in Evaluate() 265 predictors.n_rows, batchSize, false, true); in Evaluate() 329 inputSize = predictors.n_rows; in EvaluateWithGradient() [all …]
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H A D | ffn_impl.hpp | 58 arma::mat predictors, arma::mat responses) in ResetData() argument 61 this->predictors = std::move(predictors); in ResetData() 109 arma::mat predictors, in Train() argument 132 arma::mat predictors, in Train() argument 232 Forward(arma::mat(predictors.colptr(0), predictors.n_rows, 1, false, true)); in Predict() 241 Forward(arma::mat(predictors.colptr(i), predictors.n_rows, 1, false, true)); in Predict() 264 Forward(predictors); in Evaluate() 404 math::ShuffleData(predictors, responses, predictors, responses); in Shuffle() 607 std::swap(predictors, network.predictors); in Swap() 628 predictors(network.predictors), in FFN() [all …]
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H A D | brnn_impl.hpp | 124 arma::cube predictors, in Train() argument 130 this->predictors = std::move(predictors); in Train() 159 arma::cube predictors, in Train() argument 164 this->predictors = std::move(predictors); in Train() 225 size_t(predictors.n_cols - begin)); in Predict() 229 predictors.slice(seqNum).colptr(begin), in Predict() 288 inputSize = predictors.n_rows; in Evaluate() 306 predictors.slice(seqNum).colptr(begin), in Evaluate() 407 inputSize = predictors.n_rows; in EvaluateWithGradient() 424 predictors.slice(seqNum).colptr(begin), in EvaluateWithGradient() [all …]
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/dports/devel/R-cran-caret/caret/R/ |
H A D | predictors.R | 38 if(!is.null(code$predictors)){ 42 out <- code$predictors(x$finalModel, ...) 45 out <- predictors(x$terms, ...) 57 if(!is.null(code$predictors)){ 61 out <- code$predictors(x, ...) 64 out <- predictors(x$terms, ...) 68 out <- if(hasTerms(x)) predictors(x$terms) else NA 119 out <- lapply(x, predictors)
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/dports/deskutils/presage/presage-0.9.1/src/lib/core/ |
H A D | predictorRegistry.cpp | 85 for (std::vector<Predictor*>::const_iterator it = predictors.begin(); in setPredictors() 86 it != predictors.end(); in setPredictors() 194 predictors.push_back (predictor); in addPredictor() 207 std::vector<Predictor*>::iterator it = predictors.begin(); in removePredictor() 208 while (it != predictors.end()) in removePredictor() 213 it = predictors.erase(it); in removePredictor() 225 for (size_t i = 0; i < predictors.size(); i++) { in removePredictors() 226 logger << DEBUG << "Removing predictor: " << predictors[i]->getName() << endl; in removePredictors() 227 delete predictors[i]; in removePredictors() 229 predictors.clear(); in removePredictors() [all …]
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/dports/math/mlpack/mlpack-3.4.2/src/mlpack/methods/ann/gan/ |
H A D | gan_impl.hpp | 76 predictors(network.predictors), in GAN() 109 predictors(std::move(network.predictors)), in GAN() 158 this->discriminator.predictors = arma::mat(this->predictors.memptr(), in ResetData() 159 this->predictors.n_rows, this->predictors.n_cols, false, false); in ResetData() 167 this->generator.predictors.set_size(noiseDim, batchSize); in ResetData() 256 currentInput = arma::mat(predictors.memptr() + (i * predictors.n_rows), in Evaluate() 257 predictors.n_rows, batchSize, false, false); in Evaluate() 270 predictors.cols(numFunctions, numFunctions + batchSize - 1) = in Evaluate() 272 discriminator.Forward(predictors.cols(numFunctions, in Evaluate() 344 predictors.cols(numFunctions, numFunctions + batchSize - 1) = in EvaluateWithGradient() [all …]
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H A D | wgangp_impl.hpp | 49 currentInput = arma::mat(predictors.memptr() + (i * predictors.n_rows), in Evaluate() 50 predictors.n_rows, batchSize, false, false); in Evaluate() 65 predictors.cols(numFunctions, numFunctions + batchSize - 1) = in Evaluate() 67 discriminator.Forward(std::move(predictors.cols(numFunctions, in Evaluate() 81 predictors.cols(numFunctions, numFunctions + batchSize - 1) = in Evaluate() 144 currentInput = arma::mat(predictors.memptr() + (i * predictors.n_rows), in EvaluateWithGradient() 145 predictors.n_rows, batchSize, false, false); in EvaluateWithGradient() 158 predictors.cols(numFunctions, numFunctions + batchSize - 1) = in EvaluateWithGradient() 166 predictors.cols(numFunctions, numFunctions + batchSize - 1) = in EvaluateWithGradient()
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/dports/math/R-cran-VGAM/VGAM/R/ |
H A D | fittedvlm.R | 98 object@predictors 100 if (!is.matrix(object@predictors) || !length(object@predictors)) 103 if (ncol(object@predictors) == 1) { 104 c(object@predictors) 107 c(object@predictors)
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/dports/www/chromium-legacy/chromium-88.0.4324.182/chrome/browser/predictors/ |
H A D | loading_predictor_config_unittest.cc | 15 namespace predictors { namespace 32 feature_list.InitAndEnableFeature(predictors::kSpeculativePreconnectFeature); in TEST_F() 42 feature_list.InitAndDisableFeature(predictors::kSpeculativePreconnectFeature); in TEST_F() 52 feature_list.InitAndEnableFeature(predictors::kSpeculativePreconnectFeature); in TEST_F() 62 feature_list.InitAndEnableFeature(predictors::kSpeculativePreconnectFeature); in TEST_F() 73 feature_list.InitAndEnableFeature(predictors::kSpeculativePreconnectFeature); in TEST_F()
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/dports/www/chromium-legacy/chromium-88.0.4324.182/chrome/browser/page_load_metrics/observers/ |
H A D | loading_predictor_page_load_metrics_observer.h | 15 namespace predictors { 42 predictors::ResourcePrefetchPredictor* predictor, 43 predictors::LoadingDataCollector* collector); 59 predictors::ResourcePrefetchPredictor* predictor_; 60 predictors::LoadingDataCollector* collector_;
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