/dports/graphics/colmap/colmap-3.6/src/optim/ |
H A D | loransac.h | 51 template <typename Estimator, typename LocalEstimator, 70 using RANSAC<Estimator, SupportMeasurer, Sampler>::estimator; 72 using RANSAC<Estimator, SupportMeasurer, Sampler>::sampler; 76 using RANSAC<Estimator, SupportMeasurer, Sampler>::options_; 87 : RANSAC<Estimator, SupportMeasurer, Sampler>(options) {} in LORANSAC() 93 const std::vector<typename Estimator::X_t>& X, in Estimate() 94 const std::vector<typename Estimator::Y_t>& Y) { in Estimate() 103 if (num_samples < Estimator::kMinNumSamples) { in Estimate() 108 typename Estimator::M_t best_model; in Estimate() 120 std::vector<typename Estimator::X_t> X_rand(Estimator::kMinNumSamples); in Estimate() [all …]
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H A D | ransac.h | 98 typename Estimator::M_t model; 131 Estimator estimator; 144 RANSAC<Estimator, SupportMeasurer, Sampler>::RANSAC( in RANSAC() 179 typename RANSAC<Estimator, SupportMeasurer, Sampler>::Report 180 RANSAC<Estimator, SupportMeasurer, Sampler>::Estimate( in Estimate() 181 const std::vector<typename Estimator::X_t>& X, in Estimate() 182 const std::vector<typename Estimator::Y_t>& Y) { in Estimate() 191 if (num_samples < Estimator::kMinNumSamples) { in Estimate() 196 typename Estimator::M_t best_model; in Estimate() 204 std::vector<typename Estimator::X_t> X_rand(Estimator::kMinNumSamples); in Estimate() [all …]
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/dports/science/py-scikit-learn/scikit-learn-1.0.2/sklearn/tests/ |
H A D | test_docstring_parameters.py | 182 elif Estimator.__name__ == "Pipeline": 188 def _construct_sparse_coder(Estimator): argument 202 doc = docscrape.ClassDoc(Estimator) 205 if Estimator.__name__ in ( 212 elif Estimator.__name__ in ( 227 elif Estimator.__name__ == "CCA" or Estimator.__name__.startswith("PLS"): 230 elif Estimator.__name__ in ( 238 if Estimator.__name__ in ( 250 if Estimator.__name__ == "NMF": 254 if Estimator.__name__ == "TSNE": [all …]
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H A D | test_docstrings.py | 213 for name, Estimator in estimators: 218 for name in dir(Estimator): 221 method_obj = getattr(Estimator, name) 227 yield Estimator, method 275 def filter_errors(errors, method, Estimator=None): argument 299 method_obj = getattr(Estimator, method) 388 def test_docstring(Estimator, method, request): argument 389 base_import_path = Estimator.__module__ 390 import_path = [base_import_path, Estimator.__name__] 398 res["errors"] = list(filter_errors(res["errors"], method, Estimator=Estimator)) [all …]
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H A D | test_metaestimators.py | 194 for _, Estimator in sorted(all_estimators()): 195 sig = set(signature(Estimator).parameters) 198 if is_regressor(Estimator): 208 yield Estimator(estimator, param_grid, **extra_params) 210 yield Estimator(estimator) 221 yield Estimator(transformer_list) 225 if is_regressor(Estimator): 238 yield Estimator(estimator)
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/dports/science/agrum/aGrUM-29e540d8169268e8fe5d5c69bc4b2b1290f12320/src/agrum/BN/inference/tools/ |
H A D | estimator_tpl.h | 33 Estimator< GUM_SCALAR >::Estimator() { in Estimator() function 34 GUM_CONSTRUCTOR(Estimator); in Estimator() 42 Estimator< GUM_SCALAR >::Estimator(const IBayesNet< GUM_SCALAR >* bn) : Estimator() { in Estimator() function 49 GUM_CONSTRUCTOR(Estimator); in Estimator() 54 INLINE Estimator< GUM_SCALAR >::~Estimator() { in ~Estimator() 55 GUM_DESTRUCTOR(Estimator); in ~Estimator() 64 void Estimator< GUM_SCALAR >::setFromBN(const IBayesNet< GUM_SCALAR >* bn, in setFromBN() 107 void Estimator< GUM_SCALAR >::update(Instantiation I, GUM_SCALAR w) { in update() 142 GUM_SCALAR Estimator< GUM_SCALAR >::EV(std::string name, Idx val) { in EV() 160 GUM_SCALAR Estimator< GUM_SCALAR >::confidence() { in confidence() [all …]
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H A D | estimator.h | 39 class Estimator { 52 Estimator(); 57 explicit Estimator(const IBayesNet< GUM_SCALAR >* bn); 60 ~Estimator(); 161 extern template class Estimator< double >;
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/dports/benchmarks/vegeta/vegeta-12.8.4/vendor/github.com/streadway/quantile/ |
H A D | quantile.go | 77 type Estimator struct { struct 117 func New(invariants ...Estimate) *Estimator { 122 return &Estimator{ 131 func (est *Estimator) Add(value float64) { argument 140 func (est *Estimator) Get(quantile float64) float64 { argument 167 func (est *Estimator) Samples() int { argument 172 func (est *Estimator) invariant(rank float64, n float64) float64 { argument 206 func (est *Estimator) recycle(old *item) { argument 215 func (est *Estimator) update(batch []float64) { argument 248 func (est *Estimator) compress() { argument [all …]
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/dports/graphics/hugin/hugin-2020.0.0/src/hugin_base/vigra_ext/ |
H A D | ransac.h | 94 template<class Estimator, class S, class T> 97 const Estimator & paramEstimator , 125 template<class Estimator, class S, class T> 127 const Estimator & paramEstimator , 137 template<class Estimator, class T> 146 template<class Estimator, class T, class S> 174 template<class Estimator, class S, class T> 177 const Estimator & paramEstimator, in compute() 326 template<class Estimator, class S, class T> 364 template<class Estimator, class T> [all …]
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/dports/math/R-cran-matrixStats/matrixStats/vignettes/ |
H A D | matrixStats-methods.md.rsp | 96 "Estimator" = "Weighted sample mean", 103 "Estimator" = "Mean", 110 "Estimator" = "Median", 117 "Estimator" = "Weighted median", 124 "Estimator" = "Sample variance", 131 "Estimator" = "Weighted sample variance", 188 "Estimator" = "Quantile", 209 "Estimator" = "Range", 216 "Estimator" = "Minimum", 223 "Estimator" = "Maximum", [all …]
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/dports/math/R-cran-matrixStats/matrixStats/inst/doc/ |
H A D | matrixStats-methods.md.rsp | 96 "Estimator" = "Weighted sample mean", 103 "Estimator" = "Mean", 110 "Estimator" = "Median", 117 "Estimator" = "Weighted median", 124 "Estimator" = "Sample variance", 131 "Estimator" = "Weighted sample variance", 188 "Estimator" = "Quantile", 209 "Estimator" = "Range", 216 "Estimator" = "Minimum", 223 "Estimator" = "Maximum", [all …]
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/dports/misc/py-mxnet/incubator-mxnet-1.9.0/tests/python/unittest/ |
H A D | test_gluon_estimator.py | 64 est = Estimator(net=net, 94 est = Estimator(net=net, 131 est = Estimator(net=net, 202 est = Estimator(net=net, 210 est = Estimator(net=net, 226 est = Estimator(net=net, 255 est = Estimator(net=net, 262 est = Estimator(net=net, 338 est = Estimator(net=net, 389 est = Estimator(net=net, [all …]
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H A D | test_gluon_event_handler.py | 88 est = estimator.Estimator(net, loss=ce_loss, train_metrics=acc) 106 est = estimator.Estimator(net, loss=ce_loss, train_metrics=acc) 134 est = estimator.Estimator(net, loss=ce_loss, train_metrics=acc) 159 est = estimator.Estimator(net, loss=ce_loss, train_metrics=acc) 183 est = estimator.Estimator(net, loss=ce_loss, train_metrics=acc) 230 est = estimator.Estimator(net, loss=ce_loss, train_metrics=acc) 254 est = estimator.Estimator(net=net, 279 est = estimator.Estimator(net=net, 303 est = estimator.Estimator(net, loss=ce_loss, train_metrics=acc) 309 est = estimator.Estimator(net, loss=ce_loss, train_metrics=acc) [all …]
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/dports/misc/mxnet/incubator-mxnet-1.9.0/tests/python/unittest/ |
H A D | test_gluon_estimator.py | 64 est = Estimator(net=net, 94 est = Estimator(net=net, 131 est = Estimator(net=net, 202 est = Estimator(net=net, 210 est = Estimator(net=net, 226 est = Estimator(net=net, 255 est = Estimator(net=net, 262 est = Estimator(net=net, 338 est = Estimator(net=net, 389 est = Estimator(net=net, [all …]
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H A D | test_gluon_event_handler.py | 88 est = estimator.Estimator(net, loss=ce_loss, train_metrics=acc) 106 est = estimator.Estimator(net, loss=ce_loss, train_metrics=acc) 134 est = estimator.Estimator(net, loss=ce_loss, train_metrics=acc) 159 est = estimator.Estimator(net, loss=ce_loss, train_metrics=acc) 183 est = estimator.Estimator(net, loss=ce_loss, train_metrics=acc) 230 est = estimator.Estimator(net, loss=ce_loss, train_metrics=acc) 254 est = estimator.Estimator(net=net, 279 est = estimator.Estimator(net=net, 303 est = estimator.Estimator(net, loss=ce_loss, train_metrics=acc) 309 est = estimator.Estimator(net, loss=ce_loss, train_metrics=acc) [all …]
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/dports/science/py-scikit-learn/scikit-learn-1.0.2/sklearn/cluster/tests/ |
H A D | test_k_means.py | 287 def test_all_init(Estimator, data, init): argument 290 km = Estimator( 319 km_c = Estimator( 322 km_f = Estimator( 595 def test_score_max_iter(Estimator): argument 642 def test_dense_sparse(Estimator): argument 686 if Estimator is MiniBatchKMeans: 698 if Estimator is MiniBatchKMeans: 704 def test_transform(Estimator): argument 722 def test_fit_transform(Estimator): argument [all …]
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/dports/www/moodle310/moodle/lib/mlbackend/php/phpml/src/Phpml/ |
H A D | Pipeline.php | 7 class Pipeline implements Estimator 15 * @var Estimator 22 public function __construct(array $transformers, Estimator $estimator) 36 public function setEstimator(Estimator $estimator): void 49 public function getEstimator(): Estimator
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/dports/www/moodle311/moodle/lib/mlbackend/php/phpml/src/Phpml/ |
H A D | Pipeline.php | 7 class Pipeline implements Estimator 15 * @var Estimator 22 public function __construct(array $transformers, Estimator $estimator) 36 public function setEstimator(Estimator $estimator): void 49 public function getEstimator(): Estimator
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/dports/www/moodle39/moodle/lib/mlbackend/php/phpml/src/Phpml/ |
H A D | Pipeline.php | 7 class Pipeline implements Estimator 15 * @var Estimator 22 public function __construct(array $transformers, Estimator $estimator) 36 public function setEstimator(Estimator $estimator): void 49 public function getEstimator(): Estimator
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/dports/devel/spark/spark-2.1.1/docs/ |
H A D | ml-pipeline.md | 48 * **[`Estimator`](ml-pipeline.html#estimators)**: An `Estimator` is an algorithm which can be fit o… 88 For example, a learning algorithm such as `LogisticRegression` is an `Estimator`, and calling 107 `PipelineStage`s (`Transformer`s and `Estimator`s) to be run in a specific order. 138 A `Pipeline` is an `Estimator`. 175 MLlib `Estimator`s and `Transformer`s use a uniform API for specifying parameters. 187 Parameters belong to specific instances of `Estimator`s and `Transformer`s. 203 ## Example: Estimator, Transformer, and Param 205 This example covers the concepts of `Estimator`, `Transformer`, and `Param`. 211 Refer to the [`Estimator` Scala docs](api/scala/index.html#org.apache.spark.ml.Estimator), 220 Refer to the [`Estimator` Java docs](api/java/org/apache/spark/ml/Estimator.html), [all …]
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/dports/www/firefox-legacy/firefox-52.8.0esr/widget/gonk/libui/ |
H A D | VelocityTracker.h | 37 struct Estimator { struct 96 bool getEstimator(uint32_t id, Estimator* outEstimator) const; 132 virtual bool getEstimator(uint32_t id, VelocityTracker::Estimator* outEstimator) const = 0; 164 virtual bool getEstimator(uint32_t id, VelocityTracker::Estimator* outEstimator) const; 207 virtual bool getEstimator(uint32_t id, VelocityTracker::Estimator* outEstimator) const; 225 void populateEstimator(const State& state, VelocityTracker::Estimator* outEstimator) const; 241 virtual bool getEstimator(uint32_t id, VelocityTracker::Estimator* outEstimator) const;
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/dports/mail/nextcloud-mail/mail/vendor/rubix/ml/src/Backends/Tasks/ |
H A D | Predict.php | 5 use Rubix\ML\Estimator; alias 28 public static function predict(Estimator $estimator, Dataset $dataset) : array 37 public function __construct(Estimator $estimator, Dataset $dataset)
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/dports/games/widelands/widelands-build21/src/economy/ |
H A D | routeastar.h | 76 using Estimator = Est_; member 78 RouteAStar(Router& router, WareWorker type, const Estimator& est = Estimator()); 84 Estimator estimator_; 93 RouteAStar<Est_>::RouteAStar(Router& router, WareWorker type, const Estimator& est) in RouteAStar()
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/dports/mail/nextcloud-mail/mail/vendor/rubix/ml/src/Specifications/ |
H A D | EstimatorIsCompatibleWithMetric.php | 5 use Rubix\ML\Estimator; alias 37 public static function with(Estimator $estimator, Metric $metric) : self 46 public function __construct(Estimator $estimator, Metric $metric)
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H A D | SamplesAreCompatibleWithEstimator.php | 5 use Rubix\ML\Estimator; alias 37 public static function with(Dataset $dataset, Estimator $estimator) : self 46 public function __construct(Dataset $dataset, Estimator $estimator)
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