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/dports/graphics/colmap/colmap-3.6/src/optim/
H A Dloransac.h51 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()
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H A Dransac.h98 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()
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/dports/science/py-scikit-learn/scikit-learn-1.0.2/sklearn/tests/
H A Dtest_docstring_parameters.py182 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":
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H A Dtest_docstrings.py213 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))
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H A Dtest_metaestimators.py194 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)
/dports/science/agrum/aGrUM-29e540d8169268e8fe5d5c69bc4b2b1290f12320/src/agrum/BN/inference/tools/
H A Destimator_tpl.h33 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()
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H A Destimator.h39 class Estimator {
52 Estimator();
57 explicit Estimator(const IBayesNet< GUM_SCALAR >* bn);
60 ~Estimator();
161 extern template class Estimator< double >;
/dports/benchmarks/vegeta/vegeta-12.8.4/vendor/github.com/streadway/quantile/
H A Dquantile.go77 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
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/dports/graphics/hugin/hugin-2020.0.0/src/hugin_base/vigra_ext/
H A Dransac.h94 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>
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/dports/math/R-cran-matrixStats/matrixStats/vignettes/
H A DmatrixStats-methods.md.rsp96 "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",
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/dports/math/R-cran-matrixStats/matrixStats/inst/doc/
H A DmatrixStats-methods.md.rsp96 "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",
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/dports/misc/py-mxnet/incubator-mxnet-1.9.0/tests/python/unittest/
H A Dtest_gluon_estimator.py64 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,
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H A Dtest_gluon_event_handler.py88 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)
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/dports/misc/mxnet/incubator-mxnet-1.9.0/tests/python/unittest/
H A Dtest_gluon_estimator.py64 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,
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H A Dtest_gluon_event_handler.py88 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)
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/dports/science/py-scikit-learn/scikit-learn-1.0.2/sklearn/cluster/tests/
H A Dtest_k_means.py287 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
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/dports/www/moodle310/moodle/lib/mlbackend/php/phpml/src/Phpml/
H A DPipeline.php7 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
/dports/www/moodle311/moodle/lib/mlbackend/php/phpml/src/Phpml/
H A DPipeline.php7 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
/dports/www/moodle39/moodle/lib/mlbackend/php/phpml/src/Phpml/
H A DPipeline.php7 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
/dports/devel/spark/spark-2.1.1/docs/
H A Dml-pipeline.md48 * **[`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),
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/dports/www/firefox-legacy/firefox-52.8.0esr/widget/gonk/libui/
H A DVelocityTracker.h37 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;
/dports/mail/nextcloud-mail/mail/vendor/rubix/ml/src/Backends/Tasks/
H A DPredict.php5 use Rubix\ML\Estimator; alias
28 public static function predict(Estimator $estimator, Dataset $dataset) : array
37 public function __construct(Estimator $estimator, Dataset $dataset)
/dports/games/widelands/widelands-build21/src/economy/
H A Drouteastar.h76 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()
/dports/mail/nextcloud-mail/mail/vendor/rubix/ml/src/Specifications/
H A DEstimatorIsCompatibleWithMetric.php5 use Rubix\ML\Estimator; alias
37 public static function with(Estimator $estimator, Metric $metric) : self
46 public function __construct(Estimator $estimator, Metric $metric)
H A DSamplesAreCompatibleWithEstimator.php5 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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