Upgrading scikit-learn 0.19 to 0.20
Unknown0.19.2 → 0.20.4
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Adds numpy >=1.8.2, scipy >=0.13.3.
Installs 2 packages in all (was 0).
API changes
Generated by DepDelta from published Python source. Not mixed with prose notes.
- added:
export config_context - added:
export get_config - added:
export set_config - added:
export show_versions
- added:
class OutlierMixin(object) - added:
function is_outlier_detector(estimator) - added:
method OutlierMixin.fit_predict(X, y=…)
- added:
constructor FeatureAgglomeration(n_clusters=…, affinity=…, memory=…, connectivity=…, compute_full_tree=…, linkage=…, pooling_func=…)
- changed:
function k_means(X, n_clusters, init=…, precompute_distances=…, n_init=…, max_iter=…, verbose=…, tol=…, random_state=…, copy_x=…, n_jobs=…, algorithm=…, return_n_iter=…) → function k_means(X, n_clusters, sample_weight=…, init=…, precompute_distances=…, n_init=…, max_iter=…, verbose=…, tol=…, random_state=…, copy_x=…, n_jobs=…, algorithm=…, return_n_iter=…) - changed:
method KMeans.fit(X, y=…) → method KMeans.fit(X, y=…, sample_weight=…) - changed:
method KMeans.fit_predict(X, y=…) → method KMeans.fit_predict(X, y=…, sample_weight=…) - changed:
method KMeans.fit_transform(X, y=…) → method KMeans.fit_transform(X, y=…, sample_weight=…) - changed:
method KMeans.predict(X) → method KMeans.predict(X, sample_weight=…) - changed:
method KMeans.score(X, y=…) → method KMeans.score(X, y=…, sample_weight=…) - changed:
method MiniBatchKMeans.fit(X, y=…) → method MiniBatchKMeans.fit(X, y=…, sample_weight=…) - changed:
method MiniBatchKMeans.partial_fit(X, y=…) → method MiniBatchKMeans.partial_fit(X, y=…, sample_weight=…) - changed:
method MiniBatchKMeans.predict(X) → method MiniBatchKMeans.predict(X, sample_weight=…)
- added:
export ColumnTransformer - added:
export TransformedTargetRegressor - added:
export make_column_transformer
- added:
export GraphicalLasso - added:
export GraphicalLassoCV - added:
export graphical_lasso
- added:
class EllipticEnvelope(MinCovDet, OutlierMixin) - added:
constructor EllipticEnvelope(store_precision=…, assume_centered=…, support_fraction=…, contamination=…, random_state=…) - added:
method EllipticEnvelope.decision_function(X, raw_values=…) - added:
method EllipticEnvelope.fit(X, y=…) - added:
method EllipticEnvelope.predict(X) - added:
method EllipticEnvelope.score(X, y, sample_weight=…) - added:
method EllipticEnvelope.score_samples(X) - added:
property EllipticEnvelope.threshold_
- changed:
method EmpiricalCovariance.mahalanobis(observations) → method EmpiricalCovariance.mahalanobis(X)
- removed:
constructor GraphLasso(alpha=…, mode=…, tol=…, enet_tol=…, max_iter=…, verbose=…, assume_centered=…) - removed:
constructor GraphLassoCV(alphas=…, n_refinements=…, cv=…, tol=…, enet_tol=…, max_iter=…, mode=…, n_jobs=…, verbose=…, assume_centered=…) - removed:
function graph_lasso_path(X, alphas, cov_init=…, X_test=…, mode=…, tol=…, enet_tol=…, max_iter=…, verbose=…) - removed:
method GraphLasso.fit(X, y=…) - removed:
method GraphLassoCV.fit(X, y=…) - removed:
property GraphLassoCV.grid_scores - changed:
class GraphLasso(EmpiricalCovariance) → class GraphLasso(GraphicalLasso) - changed:
class GraphLassoCV(GraphLasso) → class GraphLassoCV(GraphicalLassoCV) - added:
class GraphicalLasso(EmpiricalCovariance) - added:
class GraphicalLassoCV(GraphicalLasso) - added:
constructor GraphicalLasso(alpha=…, mode=…, tol=…, enet_tol=…, max_iter=…, verbose=…, assume_centered=…) - added:
constructor GraphicalLassoCV(alphas=…, n_refinements=…, cv=…, tol=…, enet_tol=…, max_iter=…, mode=…, n_jobs=…, verbose=…, assume_centered=…) - added:
function graphical_lasso(emp_cov, alpha, cov_init=…, mode=…, tol=…, enet_tol=…, max_iter=…, verbose=…, return_costs=…, eps=…, return_n_iter=…) - added:
function graphical_lasso_path(X, alphas, cov_init=…, X_test=…, mode=…, tol=…, enet_tol=…, max_iter=…, verbose=…) - added:
method GraphicalLasso.fit(X, y=…) - added:
method GraphicalLassoCV.fit(X, y=…) - added:
property GraphicalLassoCV.grid_scores
- removed:
class EllipticEnvelope(MinCovDet) - removed:
constructor EllipticEnvelope(store_precision=…, assume_centered=…, support_fraction=…, contamination=…, random_state=…) - removed:
method EllipticEnvelope.decision_function(X, raw_values=…) - removed:
method EllipticEnvelope.fit(X, y=…) - removed:
method EllipticEnvelope.predict(X) - removed:
method EllipticEnvelope.score(X, y, sample_weight=…)
- changed:
class CCA(_PLS) → class CCA(_PLS, _UnstableArchMixin)
- removed:
class KFold(_BaseKFold) - removed:
class LabelKFold(_BaseKFold) - removed:
class LabelShuffleSplit(ShuffleSplit) - removed:
class LeaveOneLabelOut(_PartitionIterator) - removed:
class LeaveOneOut(_PartitionIterator) - removed:
class LeavePLabelOut(_PartitionIterator) - removed:
class LeavePOut(_PartitionIterator) - removed:
class PredefinedSplit(_PartitionIterator) - removed:
class ShuffleSplit(BaseShuffleSplit) - removed:
class StratifiedKFold(_BaseKFold) - removed:
class StratifiedShuffleSplit(BaseShuffleSplit) - removed:
constructor KFold(n, n_folds=…, shuffle=…, random_state=…) - removed:
constructor LabelKFold(labels, n_folds=…) - removed:
constructor LabelShuffleSplit(labels, n_iter=…, test_size=…, train_size=…, random_state=…) - removed:
constructor LeaveOneLabelOut(labels) - removed:
constructor LeavePLabelOut(labels, p) - removed:
constructor LeavePOut(n, p) - removed:
constructor PredefinedSplit(test_fold) - removed:
constructor StratifiedKFold(y, n_folds=…, shuffle=…, random_state=…) - removed:
constructor StratifiedShuffleSplit(y, n_iter=…, test_size=…, train_size=…, random_state=…) - removed:
function check_cv(cv, X=…, y=…, classifier=…) - removed:
function cross_val_predict(estimator, X, y=…, cv=…, n_jobs=…, verbose=…, fit_params=…, pre_dispatch=…) - removed:
function cross_val_score(estimator, X, y=…, scoring=…, cv=…, n_jobs=…, verbose=…, fit_params=…, pre_dispatch=…) - removed:
function permutation_test_score(estimator, X, y, cv=…, n_permutations=…, n_jobs=…, labels=…, random_state=…, verbose=…, scoring=…) - removed:
function train_test_split(*arrays, **options)
- added:
export fetch_openml
- removed:
variable MODULE_DOCS - changed:
function fetch_california_housing(data_home=…, download_if_missing=…) → function fetch_california_housing(data_home=…, download_if_missing=…, return_X_y=…)
- changed:
function fetch_covtype(data_home=…, download_if_missing=…, random_state=…, shuffle=…) → function fetch_covtype(data_home=…, download_if_missing=…, random_state=…, shuffle=…, return_X_y=…)
- changed:
function fetch_kddcup99(subset=…, data_home=…, shuffle=…, random_state=…, percent10=…, download_if_missing=…) → function fetch_kddcup99(subset=…, data_home=…, shuffle=…, random_state=…, percent10=…, download_if_missing=…, return_X_y=…)
- removed:
function check_fetch_lfw(data_home=…, funneled=…, download_if_missing=…) - changed:
function fetch_lfw_people(data_home=…, funneled=…, resize=…, min_faces_per_person=…, color=…, slice_=…, download_if_missing=…) → function fetch_lfw_people(data_home=…, funneled=…, resize=…, min_faces_per_person=…, color=…, slice_=…, download_if_missing=…, return_X_y=…)
- removed:
variable MODULE_DOCS
- added:
function fetch_openml(name=…, version=…, data_id=…, data_home=…, target_column=…, cache=…, return_X_y=…)
- changed:
function fetch_rcv1(data_home=…, subset=…, download_if_missing=…, random_state=…, shuffle=…) → function fetch_rcv1(data_home=…, subset=…, download_if_missing=…, random_state=…, shuffle=…, return_X_y=…)
- changed:
function fetch_20newsgroups_vectorized(subset=…, remove=…, data_home=…, download_if_missing=…) → function fetch_20newsgroups_vectorized(subset=…, remove=…, data_home=…, download_if_missing=…, return_X_y=…)
- removed:
export RandomizedPCA
- changed:
constructor DictionaryLearning(n_components=…, alpha=…, max_iter=…, tol=…, fit_algorithm=…, transform_algorithm=…, transform_n_nonzero_coefs=…, transform_alpha=…, n_jobs=…, code_init=…, dict_init=…, verbose=…, split_sign=…, random_state=…) → constructor DictionaryLearning(n_components=…, alpha=…, max_iter=…, tol=…, fit_algorithm=…, transform_algorithm=…, transform_n_nonzero_coefs=…, transform_alpha=…, n_jobs=…, code_init=…, dict_init=…, verbose=…, split_sign=…, random_state=…, positive_code=…, positive_dict=…) - changed:
constructor MiniBatchDictionaryLearning(n_components=…, alpha=…, n_iter=…, fit_algorithm=…, n_jobs=…, batch_size=…, shuffle=…, dict_init=…, transform_algorithm=…, transform_n_nonzero_coefs=…, transform_alpha=…, verbose=…, split_sign=…, random_state=…) → constructor MiniBatchDictionaryLearning(n_components=…, alpha=…, n_iter=…, fit_algorithm=…, n_jobs=…, batch_size=…, shuffle=…, dict_init=…, transform_algorithm=…, transform_n_nonzero_coefs=…, transform_alpha=…, verbose=…, split_sign=…, random_state=…, positive_code=…, positive_dict=…) - changed:
constructor SparseCoder(dictionary, transform_algorithm=…, transform_n_nonzero_coefs=…, transform_alpha=…, split_sign=…, n_jobs=…) → constructor SparseCoder(dictionary, transform_algorithm=…, transform_n_nonzero_coefs=…, transform_alpha=…, split_sign=…, n_jobs=…, positive_code=…) - changed:
function dict_learning(X, n_components, alpha, max_iter=…, tol=…, method=…, n_jobs=…, dict_init=…, code_init=…, callback=…, verbose=…, random_state=…, return_n_iter=…) → function dict_learning(X, n_components, alpha, max_iter=…, tol=…, method=…, n_jobs=…, dict_init=…, code_init=…, callback=…, verbose=…, random_state=…, return_n_iter=…, positive_dict=…, positive_code=…) - changed:
function dict_learning_online(X, n_components=…, alpha=…, n_iter=…, return_code=…, dict_init=…, callback=…, batch_size=…, verbose=…, shuffle=…, n_jobs=…, method=…, iter_offset=…, random_state=…, return_inner_stats=…, inner_stats=…, return_n_iter=…) → function dict_learning_online(X, n_components=…, alpha=…, n_iter=…, return_code=…, dict_init=…, callback=…, batch_size=…, verbose=…, shuffle=…, n_jobs=…, method=…, iter_offset=…, random_state=…, return_inner_stats=…, inner_stats=…, return_n_iter=…, positive_dict=…, positive_code=…) - changed:
function sparse_encode(X, dictionary, gram=…, cov=…, algorithm=…, n_nonzero_coefs=…, alpha=…, copy_cov=…, init=…, max_iter=…, n_jobs=…, check_input=…, verbose=…) → function sparse_encode(X, dictionary, gram=…, cov=…, algorithm=…, n_nonzero_coefs=…, alpha=…, copy_cov=…, init=…, max_iter=…, n_jobs=…, check_input=…, verbose=…, positive=…)
- removed:
class RandomizedPCA(BaseEstimator, TransformerMixin) - removed:
constructor RandomizedPCA(n_components=…, copy=…, iterated_power=…, whiten=…, random_state=…) - removed:
method RandomizedPCA.fit(X, y=…) - removed:
method RandomizedPCA.fit_transform(X, y=…) - removed:
method RandomizedPCA.inverse_transform(X) - removed:
method RandomizedPCA.transform(X)
- changed:
constructor MiniBatchSparsePCA(n_components=…, alpha=…, ridge_alpha=…, n_iter=…, callback=…, batch_size=…, verbose=…, shuffle=…, n_jobs=…, method=…, random_state=…) → constructor MiniBatchSparsePCA(n_components=…, alpha=…, ridge_alpha=…, n_iter=…, callback=…, batch_size=…, verbose=…, shuffle=…, n_jobs=…, method=…, random_state=…, normalize_components=…) - changed:
constructor SparsePCA(n_components=…, alpha=…, ridge_alpha=…, max_iter=…, tol=…, method=…, n_jobs=…, U_init=…, V_init=…, verbose=…, random_state=…) → constructor SparsePCA(n_components=…, alpha=…, ridge_alpha=…, max_iter=…, tol=…, method=…, n_jobs=…, U_init=…, V_init=…, verbose=…, random_state=…, normalize_components=…)
- changed:
method DummyRegressor.predict(X) → method DummyRegressor.predict(X, return_std=…) - added:
method DummyClassifier.score(X, y, sample_weight=…) - added:
method DummyRegressor.score(X, y, sample_weight=…)
- changed:
constructor BaseGradientBoosting(loss, learning_rate, n_estimators, criterion, min_samples_split, min_samples_leaf, min_weight_fraction_leaf, max_depth, min_impurity_decrease, min_impurity_split, init, subsample, max_features, random_state, alpha=…, verbose=…, max_leaf_nodes=…, warm_start=…, presort=…) → constructor BaseGradientBoosting(loss, learning_rate, n_estimators, criterion, min_samples_split, min_samples_leaf, min_weight_fraction_leaf, max_depth, min_impurity_decrease, min_impurity_split, init, subsample, max_features, random_state, alpha=…, verbose=…, max_leaf_nodes=…, warm_start=…, presort=…, validation_fraction=…, n_iter_no_change=…, tol=…) - changed:
constructor GradientBoostingClassifier(loss=…, learning_rate=…, n_estimators=…, subsample=…, criterion=…, min_samples_split=…, min_samples_leaf=…, min_weight_fraction_leaf=…, max_depth=…, min_impurity_decrease=…, min_impurity_split=…, init=…, random_state=…, max_features=…, verbose=…, max_leaf_nodes=…, warm_start=…, presort=…) → constructor GradientBoostingClassifier(loss=…, learning_rate=…, n_estimators=…, subsample=…, criterion=…, min_samples_split=…, min_samples_leaf=…, min_weight_fraction_leaf=…, max_depth=…, min_impurity_decrease=…, min_impurity_split=…, init=…, random_state=…, max_features=…, verbose=…, max_leaf_nodes=…, warm_start=…, presort=…, validation_fraction=…, n_iter_no_change=…, tol=…) - changed:
constructor GradientBoostingRegressor(loss=…, learning_rate=…, n_estimators=…, subsample=…, criterion=…, min_samples_split=…, min_samples_leaf=…, min_weight_fraction_leaf=…, max_depth=…, min_impurity_decrease=…, min_impurity_split=…, init=…, random_state=…, max_features=…, alpha=…, verbose=…, max_leaf_nodes=…, warm_start=…, presort=…) → constructor GradientBoostingRegressor(loss=…, learning_rate=…, n_estimators=…, subsample=…, criterion=…, min_samples_split=…, min_samples_leaf=…, min_weight_fraction_leaf=…, max_depth=…, min_impurity_decrease=…, min_impurity_split=…, init=…, random_state=…, max_features=…, alpha=…, verbose=…, max_leaf_nodes=…, warm_start=…, presort=…, validation_fraction=…, n_iter_no_change=…, tol=…)
- changed:
class IsolationForest(BaseBagging) → class IsolationForest(BaseBagging, OutlierMixin) - changed:
constructor IsolationForest(n_estimators=…, max_samples=…, contamination=…, max_features=…, bootstrap=…, n_jobs=…, random_state=…, verbose=…) → constructor IsolationForest(n_estimators=…, max_samples=…, contamination=…, max_features=…, bootstrap=…, n_jobs=…, behaviour=…, random_state=…, verbose=…) - added:
method IsolationForest.score_samples(X) - added:
property IsolationForest.threshold_
- added:
function pytest_ignore_collect(path, config)
- added:
export register_compressor - added:
export register_store_backend - added:
export wrap_non_picklable_objects
- removed:
variable error_access_denied - added:
variable access_denied_errors
- added:
class BZ2CompressorWrapper(CompressorWrapper) - added:
class BinaryGzipFile(BinaryZlibFile) - added:
class BinaryZlibFile(io.BufferedIOBase) - added:
class CompressorWrapper - added:
class GzipCompressorWrapper(CompressorWrapper) - added:
class LZ4CompressorWrapper(CompressorWrapper) - added:
class LZMACompressorWrapper(CompressorWrapper) - added:
class XZCompressorWrapper(LZMACompressorWrapper) - added:
class ZlibCompressorWrapper(CompressorWrapper) - added:
constructor BZ2CompressorWrapper() - added:
constructor BinaryZlibFile(filename, mode=…, compresslevel=…) - added:
constructor CompressorWrapper(obj, prefix=…, extension=…) - added:
constructor GzipCompressorWrapper() - added:
constructor LZ4CompressorWrapper() - added:
constructor LZMACompressorWrapper() - added:
constructor XZCompressorWrapper() - added:
constructor ZlibCompressorWrapper() - added:
field BZ2CompressorWrapper.extension - added:
field BZ2CompressorWrapper.prefix - added:
field BinaryGzipFile.wbits - added:
field BinaryZlibFile.wbits - added:
field LZ4CompressorWrapper.extension - added:
field LZ4CompressorWrapper.prefix - added:
field LZMACompressorWrapper.extension - added:
field LZMACompressorWrapper.prefix - added:
field XZCompressorWrapper.extension - added:
field XZCompressorWrapper.prefix - added:
function register_compressor(compressor_name, compressor, force=…) - added:
method BZ2CompressorWrapper.compressor_file(fileobj, compresslevel=…) - added:
method BZ2CompressorWrapper.decompressor_file(fileobj) - added:
method BinaryZlibFile.close() - added:
method BinaryZlibFile.fileno() - added:
method BinaryZlibFile.read(size=…) - added:
method BinaryZlibFile.readable() - added:
method BinaryZlibFile.readinto(b) - added:
method BinaryZlibFile.seek(offset, whence=…) - added:
method BinaryZlibFile.seekable() - added:
method BinaryZlibFile.tell() - added:
method BinaryZlibFile.writable() - added:
method BinaryZlibFile.write(data) - added:
method CompressorWrapper.compressor_file(fileobj, compresslevel=…) - added:
method CompressorWrapper.decompressor_file(fileobj) - added:
method LZ4CompressorWrapper.compressor_file(fileobj, compresslevel=…) - added:
method LZ4CompressorWrapper.decompressor_file(fileobj) - added:
method LZMACompressorWrapper.compressor_file(fileobj, compresslevel=…) - added:
method LZMACompressorWrapper.decompressor_file(fileobj) - added:
method XZCompressorWrapper.compressor_file(fileobj, compresslevel=…) - added:
property BinaryZlibFile.closed - added:
variable LZ4_NOT_INSTALLED_ERROR - added:
variable bz2 - added:
variable lz4 - added:
variable lzma
- added:
function delete_folder(folder_path, onerror=…) - added:
variable RM_SUBDIRS_N_RETRY - added:
variable WindowsError
- added:
function get_memmapping_executor(n_jobs, timeout=…, initializer=…, initargs=…, **backend_args)
- added:
class CloudPickler(Pickler) - added:
constructor CloudPickler(file, protocol=…) - added:
field CloudPickler.dispatch - added:
function cell_set(cell, value) - added:
function dump(obj, file, protocol=…) - added:
function dumps(obj, protocol=…) - added:
function dynamic_subimport(name, vars) - added:
function instance(cls) - added:
function is_tornado_coroutine(func) - added:
function islambda(func) - added:
function print_exec(stream) - added:
function subimport(name) - added:
method CloudPickler.dump(obj) - added:
method CloudPickler.extract_func_data(func) - added:
method CloudPickler.inject_addons() - added:
method CloudPickler.save_attrgetter(obj) - added:
method CloudPickler.save_buffer(obj) - added:
method CloudPickler.save_builtin_function(obj) - added:
method CloudPickler.save_classmethod(obj) - added:
method CloudPickler.save_codeobject(obj) - added:
method CloudPickler.save_dynamic_class(obj) - added:
method CloudPickler.save_ellipsis(obj) - added:
method CloudPickler.save_file(obj) - added:
method CloudPickler.save_function(obj, name=…) - added:
method CloudPickler.save_function_tuple(func) - added:
method CloudPickler.save_global(obj, name=…, pack=…) - added:
method CloudPickler.save_inst(obj) - added:
method CloudPickler.save_instancemethod(obj) - added:
method CloudPickler.save_itemgetter(obj) - added:
method CloudPickler.save_logger(obj) - added:
method CloudPickler.save_mappingproxy(obj) - added:
method CloudPickler.save_memoryview(obj) - added:
method CloudPickler.save_module(obj) - added:
method CloudPickler.save_not_implemented(obj) - added:
method CloudPickler.save_property(obj) - added:
method CloudPickler.save_root_logger(obj) - added:
method CloudPickler.save_weakset(obj) - added:
static method CloudPickler.extract_code_globals(co) - added:
variable DEFAULT_PROTOCOL - added:
variable DELETE_GLOBAL - added:
variable EXTENDED_ARG - added:
variable GLOBAL_OPS - added:
variable HAVE_ARGUMENT - added:
variable LOAD_GLOBAL - added:
variable PY3 - added:
variable STORE_GLOBAL - added:
variable load - added:
variable loads - added:
variable method_descriptor - added:
variable string_types
- added:
export ALL_COMPLETED - added:
export BrokenProcessPool - added:
export CancelledError - added:
export Executor - added:
export FIRST_COMPLETED - added:
export FIRST_EXCEPTION - added:
export Future - added:
export ProcessPoolExecutor - added:
export TimeoutError - added:
export as_completed - added:
export cpu_count - added:
export get_reusable_executor - added:
export set_loky_pickler - added:
export wait - added:
export wrap_non_picklable_objects
- added:
export get_context
- added:
export BaseProcess - added:
export queue - added:
export wait - added:
function set_cause(exc, cause)
- added:
class LokyContext(BaseContext) - added:
class LokyInitMainContext(LokyContext) - added:
field LokyContext.BoundedSemaphore - added:
field LokyContext.Condition - added:
field LokyContext.Event - added:
field LokyContext.Lock - added:
field LokyContext.Manager - added:
field LokyContext.Process - added:
field LokyContext.RLock - added:
field LokyContext.Semaphore - added:
field LokyContext.cpu_count - added:
field LokyInitMainContext.Process - added:
function assert_spawning(obj) - added:
function cpu_count() - added:
function get_context(method=…) - added:
function get_spawning_popen() - added:
function get_start_method() - added:
function set_spawning_popen(popen) - added:
function set_start_method(method, force=…) - added:
method LokyContext.BoundedSemaphore(value) - added:
method LokyContext.Condition(lock=…) - added:
method LokyContext.Event() - added:
method LokyContext.Lock() - added:
method LokyContext.Manager() - added:
method LokyContext.Pipe(duplex=…) - added:
method LokyContext.Queue(maxsize=…, reducers=…) - added:
method LokyContext.RLock() - added:
method LokyContext.Semaphore(value=…) - added:
method LokyContext.SimpleQueue(reducers=…) - added:
method LokyContext.get_context() - added:
method LokyContext.get_start_method() - added:
variable BaseContext - added:
variable START_METHODS - added:
variable ctx_loky - added:
variable popen_attr
- added:
function close_fds(keep_fds) - added:
function fork_exec(cmd, keep_fds) - added:
variable FileNotFoundError
- added:
class LokyManager(SyncManager) - added:
method LokyManager.start(initializer=…, initargs=…)
- added:
class Popen(object) - added:
constructor Popen(process_obj) - added:
field Popen.DupFd - added:
field Popen.method - added:
method Popen.duplicate_for_child(fd) - added:
method Popen.poll(flag=…) - added:
method Popen.terminate() - added:
method Popen.wait(timeout=…) - added:
static method Popen.thread_is_spawning()
- added:
class Popen(_Popen) - added:
constructor Popen(process_obj) - added:
field Popen.method - added:
method Popen.duplicate_for_child(handle)
- added:
class AuthenticationKey(bytes) - added:
class LokyInitMainProcess(LokyProcess) - added:
class LokyProcess(BaseProcess) - added:
constructor LokyInitMainProcess(group=…, target=…, name=…, args=…, kwargs=…, daemon=…) - added:
constructor LokyProcess(group=…, target=…, name=…, args=…, kwargs=…, daemon=…, init_main_module=…) - added:
method LokyProcess.start() - added:
property LokyProcess.authkey - added:
property LokyProcess.sentinel
- added:
class Queue(mp_Queue) - added:
class SimpleQueue(mp_SimpleQueue) - added:
constructor Queue(maxsize=…, reducers=…, ctx=…) - added:
constructor SimpleQueue(reducers=…, ctx=…) - added:
export Full - added:
method SimpleQueue.get() - added:
method SimpleQueue.put(obj)
- added:
export duplicate - added:
function dump(obj, file, reducers=…, protocol=…) - added:
function dumps(obj, reducers=…, protocol=…) - added:
function loads(buf) - added:
function set_loky_pickler(loky_pickler=…) - added:
variable register
- added:
variable ensure_running - added:
variable register - added:
variable unregister
- added:
class FileExistsError(OSError) - added:
class FileNotFoundError(OSError) - added:
class SemLock(object) - added:
class timespec(ctypes.Structure) - added:
constructor SemLock(kind, value, maxvalue, name=…, unlink_now=…) - added:
function get_ident() - added:
function raiseFromErrno() - added:
function sem_unlink(name) - added:
method SemLock.acquire(block=…, timeout=…) - added:
method SemLock.release() - added:
variable RECURSIVE_MUTEX - added:
variable SEMAPHORE - added:
variable SEM_FAILURE - added:
variable SEM_OFLAG - added:
variable SEM_PERM - added:
variable pthread
- added:
function get_executable() - added:
function get_preparation_data(name, init_main_module=…) - added:
function import_main_path(main_path) - added:
function prepare(data) - added:
variable WINEXE - added:
variable WINSERVICE - added:
variable old_main_modules
- added:
class BoundedSemaphore(Semaphore) - added:
class Condition(object) - added:
class Event(object) - added:
class Lock(SemLock) - added:
class RLock(SemLock) - added:
class Semaphore(SemLock) - added:
constructor BoundedSemaphore(value=…) - added:
constructor Condition(lock=…) - added:
constructor Event() - added:
constructor Lock() - added:
constructor RLock() - added:
constructor Semaphore(value=…) - added:
method Condition.notify() - added:
method Condition.notify_all() - added:
method Condition.wait(timeout=…) - added:
method Condition.wait_for(predicate, timeout=…) - added:
method Event.clear() - added:
method Event.is_set() - added:
method Event.set() - added:
method Event.wait(timeout=…) - added:
method Semaphore.get_value()
- added:
function get_exitcodes_terminated_worker(processes) - added:
function recursive_terminate(process, use_psutil=…) - added:
variable WIN32 - added:
variable psutil
- added:
class CallableObjectWrapper(CloudpickledObjectWrapper) - added:
class CloudpickledObjectWrapper(object) - added:
constructor CloudpickledObjectWrapper(obj, keep_wrapper=…) - added:
function wrap_non_picklable_objects(obj, keep_wrapper=…) - added:
variable WRAP_CACHE - added:
variable cloudpickle
- added:
class BrokenProcessPool(_BPPException) - added:
class LokyRecursionError(RuntimeError) - added:
class ProcessPoolExecutor(_base.Executor) - added:
class ShutdownExecutorError(RuntimeError) - added:
class TerminatedWorkerError(BrokenProcessPool) - added:
constructor ProcessPoolExecutor(max_workers=…, job_reducers=…, result_reducers=…, timeout=…, context=…, initializer=…, initargs=…) - added:
method ProcessPoolExecutor.map(fn, *iterables, **kwargs) - added:
method ProcessPoolExecutor.shutdown(wait=…, kill_workers=…) - added:
method ProcessPoolExecutor.submit(fn, *args, **kwargs) - added:
variable BrokenExecutor - added:
variable EXTRA_QUEUED_CALLS - added:
variable MAX_DEPTH - added:
variable ProcessLookupError - added:
variable process_pool_executor_at_exit
- added:
function get_reusable_executor(max_workers=…, context=…, timeout=…, kill_workers=…, reuse=…, job_reducers=…, result_reducers=…, initializer=…, initargs=…)
- added:
variable full_argspec_fields - added:
variable full_argspec_type
- removed:
field MemorizedFunc.get_output_dir - removed:
function concurrency_safe_write(to_write, filename, write_func) - removed:
variable CacheItemInfo - changed:
constructor MemorizedFunc(func, cachedir, ignore=…, mmap_mode=…, compress=…, verbose=…, timestamp=…) → constructor MemorizedFunc(func, location, backend=…, ignore=…, mmap_mode=…, compress=…, verbose=…, timestamp=…) - changed:
constructor MemorizedResult(cachedir, func, argument_hash, mmap_mode=…, verbose=…, timestamp=…, metadata=…) → constructor MemorizedResult(location, func, args_id, backend=…, mmap_mode=…, verbose=…, timestamp=…, metadata=…) - changed:
constructor Memory(cachedir, mmap_mode=…, compress=…, verbose=…, bytes_limit=…) → constructor Memory(location=…, backend=…, cachedir=…, mmap_mode=…, compress=…, verbose=…, bytes_limit=…, backend_options=…) - added:
function register_store_backend(backend_name, backend) - added:
property MemorizedResult.argument_hash - added:
property Memory.cachedir
- added:
method TransportableException.unwrap(context_message=…)
- removed:
class BinaryGzipFile(BinaryZlibFile) - removed:
class BinaryZlibFile(io.BufferedIOBase) - removed:
constructor BinaryZlibFile(filename, mode=…, compresslevel=…) - removed:
field BinaryGzipFile.wbits - removed:
field BinaryZlibFile.wbits - removed:
method BinaryZlibFile.close() - removed:
method BinaryZlibFile.fileno() - removed:
method BinaryZlibFile.read(size=…) - removed:
method BinaryZlibFile.readable() - removed:
method BinaryZlibFile.readinto(b) - removed:
method BinaryZlibFile.seek(offset, whence=…) - removed:
method BinaryZlibFile.seekable() - removed:
method BinaryZlibFile.tell() - removed:
method BinaryZlibFile.writable() - removed:
method BinaryZlibFile.write(data) - removed:
property BinaryZlibFile.closed - removed:
variable lzma
- removed:
function parallel_backend(backend, n_jobs=…, **backend_params) - changed:
constructor BatchedCalls(iterator_slice) → constructor BatchedCalls(iterator_slice, backend_and_jobs, pickle_cache=…) - changed:
constructor Parallel(n_jobs=…, backend=…, verbose=…, timeout=…, pre_dispatch=…, batch_size=…, temp_folder=…, max_nbytes=…, mmap_mode=…) → constructor Parallel(n_jobs=…, backend=…, verbose=…, timeout=…, pre_dispatch=…, batch_size=…, temp_folder=…, max_nbytes=…, mmap_mode=…, prefer=…, require=…) - changed:
function get_active_backend() → function get_active_backend(prefer=…, require=…, verbose=…) - added:
class parallel_backend(object) - added:
constructor parallel_backend(backend, n_jobs=…, **backend_params) - added:
method parallel_backend.unregister() - added:
variable DEFAULT_THREAD_BACKEND - added:
variable EXTERNAL_BACKENDS - added:
variable VALID_BACKEND_CONSTRAINTS - added:
variable VALID_BACKEND_HINTS
- removed:
class ArrayMemmapReducer(object) - removed:
class MemmapingPool(PicklingPool) - removed:
constructor ArrayMemmapReducer(max_nbytes, temp_folder, mmap_mode, verbose=…, context_id=…, prewarm=…) - removed:
constructor MemmapingPool(processes=…, temp_folder=…, max_nbytes=…, mmap_mode=…, forward_reducers=…, backward_reducers=…, verbose=…, context_id=…, prewarm=…, **kwargs) - removed:
function delete_folder(folder_path) - removed:
function has_shareable_memory(a) - removed:
function reduce_memmap(a) - removed:
method MemmapingPool.terminate() - removed:
variable FILE_PERMISSIONS - removed:
variable FOLDER_PERMISSIONS - removed:
variable SYSTEM_SHARED_MEM_FS - added:
class MemmappingPool(PicklingPool) - added:
constructor MemmappingPool(processes=…, temp_folder=…, max_nbytes=…, mmap_mode=…, forward_reducers=…, backward_reducers=…, verbose=…, context_id=…, prewarm=…, **kwargs) - added:
method MemmappingPool.terminate()
- changed:
constructor SelectFromModel(estimator, threshold=…, prefit=…, norm_order=…) → constructor SelectFromModel(estimator, threshold=…, prefit=…, norm_order=…, max_features=…)
- changed:
constructor RFECV(estimator, step=…, cv=…, scoring=…, verbose=…, n_jobs=…) → constructor RFECV(estimator, step=…, min_features_to_select=…, cv=…, scoring=…, verbose=…, n_jobs=…) - changed:
method RFECV.fit(X, y) → method RFECV.fit(X, y, groups=…)
- removed:
export GaussianProcess
- removed:
class GaussianProcess(BaseEstimator, RegressorMixin) - removed:
constructor GaussianProcess(regr=…, corr=…, beta0=…, storage_mode=…, verbose=…, theta0=…, thetaL=…, thetaU=…, optimizer=…, random_start=…, normalize=…, nugget=…, random_state=…) - removed:
function l1_cross_distances(X) - removed:
method GaussianProcess.fit(X, y) - removed:
method GaussianProcess.predict(X, eval_MSE=…, batch_size=…) - removed:
method GaussianProcess.reduced_likelihood_function(theta=…) - removed:
variable MACHINE_EPSILON
- removed:
class GridSearchCV(BaseSearchCV) - removed:
class ParameterGrid(object) - removed:
class ParameterSampler(object) - removed:
class RandomizedSearchCV(BaseSearchCV) - removed:
constructor GridSearchCV(estimator, param_grid, scoring=…, fit_params=…, n_jobs=…, iid=…, refit=…, cv=…, verbose=…, pre_dispatch=…, error_score=…) - removed:
constructor ParameterGrid(param_grid) - removed:
constructor ParameterSampler(param_distributions, n_iter, random_state=…) - removed:
constructor RandomizedSearchCV(estimator, param_distributions, n_iter=…, scoring=…, fit_params=…, n_jobs=…, iid=…, refit=…, cv=…, verbose=…, pre_dispatch=…, random_state=…, error_score=…) - removed:
function fit_grid_point(X, y, estimator, parameters, train, test, scorer, verbose, error_score=…, **fit_params) - removed:
method GridSearchCV.fit(X, y=…) - removed:
method RandomizedSearchCV.fit(X, y=…)
- added:
class MissingIndicator(BaseEstimator, TransformerMixin) - added:
class SimpleImputer(BaseEstimator, TransformerMixin) - added:
constructor MissingIndicator(missing_values=…, features=…, sparse=…, error_on_new=…) - added:
constructor SimpleImputer(missing_values=…, strategy=…, fill_value=…, verbose=…, copy=…) - added:
method MissingIndicator.fit(X, y=…) - added:
method MissingIndicator.fit_transform(X, y=…) - added:
method MissingIndicator.transform(X) - added:
method SimpleImputer.fit(X, y=…) - added:
method SimpleImputer.transform(X)
- removed:
property IsotonicRegression.X_ - removed:
property IsotonicRegression.y_
- removed:
function learning_curve(estimator, X, y, train_sizes=…, cv=…, scoring=…, exploit_incremental_learning=…, n_jobs=…, pre_dispatch=…, verbose=…, error_score=…) - removed:
function validation_curve(estimator, X, y, param_name, param_range, cv=…, scoring=…, n_jobs=…, pre_dispatch=…, verbose=…)
- removed:
function center_data(X, y, fit_intercept, normalize=…, copy=…, sample_weight=…) - removed:
function sparse_center_data(X, y, fit_intercept, normalize=…)
- changed:
method BayesianRidge.fit(X, y) → method BayesianRidge.fit(X, y, sample_weight=…)
- removed:
property LarsCV.cv_mse_path_
- added:
method LogisticRegressionCV.score(X, y, sample_weight=…)
- removed:
variable solve_triangular_args
- changed:
constructor PassiveAggressiveClassifier(C=…, fit_intercept=…, max_iter=…, tol=…, shuffle=…, verbose=…, loss=…, n_jobs=…, random_state=…, warm_start=…, class_weight=…, average=…, n_iter=…) → constructor PassiveAggressiveClassifier(C=…, fit_intercept=…, max_iter=…, tol=…, early_stopping=…, validation_fraction=…, n_iter_no_change=…, shuffle=…, verbose=…, loss=…, n_jobs=…, random_state=…, warm_start=…, class_weight=…, average=…, n_iter=…) - changed:
constructor PassiveAggressiveRegressor(C=…, fit_intercept=…, max_iter=…, tol=…, shuffle=…, verbose=…, loss=…, epsilon=…, random_state=…, warm_start=…, average=…, n_iter=…) → constructor PassiveAggressiveRegressor(C=…, fit_intercept=…, max_iter=…, tol=…, early_stopping=…, validation_fraction=…, n_iter_no_change=…, shuffle=…, verbose=…, loss=…, epsilon=…, random_state=…, warm_start=…, average=…, n_iter=…)
- changed:
constructor Perceptron(penalty=…, alpha=…, fit_intercept=…, max_iter=…, tol=…, shuffle=…, verbose=…, eta0=…, n_jobs=…, random_state=…, class_weight=…, warm_start=…, n_iter=…) → constructor Perceptron(penalty=…, alpha=…, fit_intercept=…, max_iter=…, tol=…, shuffle=…, verbose=…, eta0=…, n_jobs=…, random_state=…, early_stopping=…, validation_fraction=…, n_iter_no_change=…, class_weight=…, warm_start=…, n_iter=…)
- changed:
constructor RANSACRegressor(base_estimator=…, min_samples=…, residual_threshold=…, is_data_valid=…, is_model_valid=…, max_trials=…, max_skips=…, stop_n_inliers=…, stop_score=…, stop_probability=…, residual_metric=…, loss=…, random_state=…) → constructor RANSACRegressor(base_estimator=…, min_samples=…, residual_threshold=…, is_data_valid=…, is_model_valid=…, max_trials=…, max_skips=…, stop_n_inliers=…, stop_score=…, stop_probability=…, loss=…, random_state=…)
- changed:
constructor RidgeClassifierCV(alphas=…, fit_intercept=…, normalize=…, scoring=…, cv=…, class_weight=…) → constructor RidgeClassifierCV(alphas=…, fit_intercept=…, normalize=…, scoring=…, cv=…, class_weight=…, store_cv_values=…)
- changed:
constructor BaseSGD(loss, penalty=…, alpha=…, C=…, l1_ratio=…, fit_intercept=…, max_iter=…, tol=…, shuffle=…, verbose=…, epsilon=…, random_state=…, learning_rate=…, eta0=…, power_t=…, warm_start=…, average=…, n_iter=…) → constructor BaseSGD(loss, penalty=…, alpha=…, C=…, l1_ratio=…, fit_intercept=…, max_iter=…, tol=…, shuffle=…, verbose=…, epsilon=…, random_state=…, learning_rate=…, eta0=…, power_t=…, early_stopping=…, validation_fraction=…, n_iter_no_change=…, warm_start=…, average=…, n_iter=…) - changed:
constructor BaseSGDClassifier(loss=…, penalty=…, alpha=…, l1_ratio=…, fit_intercept=…, max_iter=…, tol=…, shuffle=…, verbose=…, epsilon=…, n_jobs=…, random_state=…, learning_rate=…, eta0=…, power_t=…, class_weight=…, warm_start=…, average=…, n_iter=…) → constructor BaseSGDClassifier(loss=…, penalty=…, alpha=…, l1_ratio=…, fit_intercept=…, max_iter=…, tol=…, shuffle=…, verbose=…, epsilon=…, n_jobs=…, random_state=…, learning_rate=…, eta0=…, power_t=…, early_stopping=…, validation_fraction=…, n_iter_no_change=…, class_weight=…, warm_start=…, average=…, n_iter=…) - changed:
constructor BaseSGDRegressor(loss=…, penalty=…, alpha=…, l1_ratio=…, fit_intercept=…, max_iter=…, tol=…, shuffle=…, verbose=…, epsilon=…, random_state=…, learning_rate=…, eta0=…, power_t=…, warm_start=…, average=…, n_iter=…) → constructor BaseSGDRegressor(loss=…, penalty=…, alpha=…, l1_ratio=…, fit_intercept=…, max_iter=…, tol=…, shuffle=…, verbose=…, epsilon=…, random_state=…, learning_rate=…, eta0=…, power_t=…, early_stopping=…, validation_fraction=…, n_iter_no_change=…, warm_start=…, average=…, n_iter=…) - changed:
constructor SGDClassifier(loss=…, penalty=…, alpha=…, l1_ratio=…, fit_intercept=…, max_iter=…, tol=…, shuffle=…, verbose=…, epsilon=…, n_jobs=…, random_state=…, learning_rate=…, eta0=…, power_t=…, class_weight=…, warm_start=…, average=…, n_iter=…) → constructor SGDClassifier(loss=…, penalty=…, alpha=…, l1_ratio=…, fit_intercept=…, max_iter=…, tol=…, shuffle=…, verbose=…, epsilon=…, n_jobs=…, random_state=…, learning_rate=…, eta0=…, power_t=…, early_stopping=…, validation_fraction=…, n_iter_no_change=…, class_weight=…, warm_start=…, average=…, n_iter=…) - changed:
constructor SGDRegressor(loss=…, penalty=…, alpha=…, l1_ratio=…, fit_intercept=…, max_iter=…, tol=…, shuffle=…, verbose=…, epsilon=…, random_state=…, learning_rate=…, eta0=…, power_t=…, warm_start=…, average=…, n_iter=…) → constructor SGDRegressor(loss=…, penalty=…, alpha=…, l1_ratio=…, fit_intercept=…, max_iter=…, tol=…, shuffle=…, verbose=…, epsilon=…, random_state=…, learning_rate=…, eta0=…, power_t=…, early_stopping=…, validation_fraction=…, n_iter_no_change=…, warm_start=…, average=…, n_iter=…) - changed:
function fit_binary(est, i, X, y, alpha, C, learning_rate, max_iter, pos_weight, neg_weight, sample_weight) → function fit_binary(est, i, X, y, alpha, C, learning_rate, max_iter, pos_weight, neg_weight, sample_weight, validation_mask=…)
- changed:
class LocallyLinearEmbedding(BaseEstimator, TransformerMixin) → class LocallyLinearEmbedding(BaseEstimator, TransformerMixin, _UnstableArchMixin)
- changed:
function trustworthiness(X, X_embedded, n_neighbors=…, precomputed=…) → function trustworthiness(X, X_embedded, n_neighbors=…, precomputed=…, metric=…)
- added:
export balanced_accuracy_score - added:
export check_scoring - added:
export davies_bouldin_score - added:
export pairwise_distances_chunked
- changed:
function classification_report(y_true, y_pred, labels=…, target_names=…, sample_weight=…, digits=…) → function classification_report(y_true, y_pred, labels=…, target_names=…, sample_weight=…, digits=…, output_dict=…) - changed:
function hamming_loss(y_true, y_pred, labels=…, sample_weight=…, classes=…) → function hamming_loss(y_true, y_pred, labels=…, sample_weight=…) - added:
function balanced_accuracy_score(y_true, y_pred, sample_weight=…, adjusted=…)
- added:
export davies_bouldin_score
- removed:
function comb2(n) - changed:
function adjusted_mutual_info_score(labels_true, labels_pred) → function adjusted_mutual_info_score(labels_true, labels_pred, average_method=…) - changed:
function normalized_mutual_info_score(labels_true, labels_pred) → function normalized_mutual_info_score(labels_true, labels_pred, average_method=…)
- added:
function davies_bouldin_score(X, labels)
- changed:
function linear_kernel(X, Y=…) → function linear_kernel(X, Y=…, dense_output=…) - added:
function pairwise_distances_chunked(X, Y=…, reduce_func=…, metric=…, n_jobs=…, working_memory=…, **kwds)
- changed:
function average_precision_score(y_true, y_score, average=…, sample_weight=…) → function average_precision_score(y_true, y_score, average=…, pos_label=…, sample_weight=…) - changed:
function label_ranking_average_precision_score(y_true, y_score) → function label_ranking_average_precision_score(y_true, y_score, sample_weight=…) - changed:
function roc_auc_score(y_true, y_score, average=…, sample_weight=…) → function roc_auc_score(y_true, y_score, average=…, sample_weight=…, max_fpr=…)
- removed:
variable deprecation_msg - removed:
variable log_loss_scorer - removed:
variable mean_absolute_error_scorer - removed:
variable mean_squared_error_scorer - removed:
variable median_absolute_error_scorer - added:
variable balanced_accuracy_scorer - added:
variable brier_score_loss_scorer
- removed:
export DPGMM - removed:
export GMM - removed:
export VBGMM - removed:
export _validate_covars - removed:
export distribute_covar_matrix_to_match_covariance_type - removed:
export log_multivariate_normal_density - removed:
export sample_gaussian
- added:
method BaseMixture.fit_predict(X, y=…)
- removed:
class DPGMM(_DPGMMBase) - removed:
class VBGMM(_DPGMMBase) - removed:
constructor DPGMM(n_components=…, covariance_type=…, alpha=…, random_state=…, tol=…, verbose=…, min_covar=…, n_iter=…, params=…, init_params=…) - removed:
constructor VBGMM(n_components=…, covariance_type=…, alpha=…, random_state=…, tol=…, verbose=…, min_covar=…, n_iter=…, params=…, init_params=…) - removed:
function digamma(x) - removed:
function gammaln(x) - removed:
function log_normalize(v, axis=…) - removed:
function wishart_log_det(a, b, detB, n_features) - removed:
function wishart_logz(v, s, dets, n_features) - removed:
method VBGMM.score_samples(X)
- removed:
class GMM(_GMMBase) - removed:
constructor GMM(n_components=…, covariance_type=…, random_state=…, tol=…, min_covar=…, n_iter=…, n_init=…, params=…, init_params=…, verbose=…) - removed:
function distribute_covar_matrix_to_match_covariance_type(tied_cv, covariance_type, n_components) - removed:
function log_multivariate_normal_density(X, means, covars, covariance_type=…) - removed:
function sample_gaussian(mean, covar, covariance_type=…, n_samples=…, random_state=…) - removed:
variable EPS
- removed:
constructor ClassifierChain(base_estimator, order=…, cv=…, random_state=…) - removed:
method ClassifierChain.predict(X) - changed:
class ClassifierChain(BaseEstimator, ClassifierMixin, MetaEstimatorMixin) → class ClassifierChain(_BaseChain, ClassifierMixin, MetaEstimatorMixin) - added:
class RegressorChain(_BaseChain, RegressorMixin, MetaEstimatorMixin) - added:
method RegressorChain.fit(X, Y)
- changed:
constructor GaussianNB(priors=…) → constructor GaussianNB(priors=…, var_smoothing=…) - added:
class ComplementNB(BaseDiscreteNB) - added:
constructor ComplementNB(alpha=…, fit_prior=…, class_prior=…, norm=…)
- added:
export VALID_METRICS - added:
export VALID_METRICS_SPARSE
- changed:
constructor NeighborsBase() → constructor NeighborsBase(n_neighbors=…, radius=…, algorithm=…, leaf_size=…, metric=…, p=…, metric_params=…, n_jobs=…)
- changed:
constructor RadiusNeighborsClassifier(radius=…, weights=…, algorithm=…, leaf_size=…, p=…, metric=…, outlier_label=…, metric_params=…, **kwargs) → constructor RadiusNeighborsClassifier(radius=…, weights=…, algorithm=…, leaf_size=…, p=…, metric=…, outlier_label=…, metric_params=…, n_jobs=…, **kwargs)
- changed:
method KernelDensity.fit(X, y=…) → method KernelDensity.fit(X, y=…, sample_weight=…)
- removed:
method LocalOutlierFactor.fit_predict(X, y=…) - changed:
class LocalOutlierFactor(NeighborsBase, KNeighborsMixin, UnsupervisedMixin) → class LocalOutlierFactor(NeighborsBase, KNeighborsMixin, UnsupervisedMixin, OutlierMixin) - changed:
constructor LocalOutlierFactor(n_neighbors=…, algorithm=…, leaf_size=…, metric=…, p=…, metric_params=…, contamination=…, n_jobs=…) → constructor LocalOutlierFactor(n_neighbors=…, algorithm=…, leaf_size=…, metric=…, p=…, metric_params=…, contamination=…, novelty=…, n_jobs=…) - added:
property LocalOutlierFactor.decision_function - added:
property LocalOutlierFactor.fit_predict - added:
property LocalOutlierFactor.predict - added:
property LocalOutlierFactor.score_samples
- changed:
constructor RadiusNeighborsRegressor(radius=…, weights=…, algorithm=…, leaf_size=…, p=…, metric=…, metric_params=…, **kwargs) → constructor RadiusNeighborsRegressor(radius=…, weights=…, algorithm=…, leaf_size=…, p=…, metric=…, metric_params=…, n_jobs=…, **kwargs)
- changed:
constructor BaseMultilayerPerceptron(hidden_layer_sizes, activation, solver, alpha, batch_size, learning_rate, learning_rate_init, power_t, max_iter, loss, shuffle, random_state, tol, verbose, warm_start, momentum, nesterovs_momentum, early_stopping, validation_fraction, beta_1, beta_2, epsilon) → constructor BaseMultilayerPerceptron(hidden_layer_sizes, activation, solver, alpha, batch_size, learning_rate, learning_rate_init, power_t, max_iter, loss, shuffle, random_state, tol, verbose, warm_start, momentum, nesterovs_momentum, early_stopping, validation_fraction, beta_1, beta_2, epsilon, n_iter_no_change) - changed:
constructor MLPClassifier(hidden_layer_sizes=…, activation=…, solver=…, alpha=…, batch_size=…, learning_rate=…, learning_rate_init=…, power_t=…, max_iter=…, shuffle=…, random_state=…, tol=…, verbose=…, warm_start=…, momentum=…, nesterovs_momentum=…, early_stopping=…, validation_fraction=…, beta_1=…, beta_2=…, epsilon=…) → constructor MLPClassifier(hidden_layer_sizes=…, activation=…, solver=…, alpha=…, batch_size=…, learning_rate=…, learning_rate_init=…, power_t=…, max_iter=…, shuffle=…, random_state=…, tol=…, verbose=…, warm_start=…, momentum=…, nesterovs_momentum=…, early_stopping=…, validation_fraction=…, beta_1=…, beta_2=…, epsilon=…, n_iter_no_change=…) - changed:
constructor MLPRegressor(hidden_layer_sizes=…, activation=…, solver=…, alpha=…, batch_size=…, learning_rate=…, learning_rate_init=…, power_t=…, max_iter=…, shuffle=…, random_state=…, tol=…, verbose=…, warm_start=…, momentum=…, nesterovs_momentum=…, early_stopping=…, validation_fraction=…, beta_1=…, beta_2=…, epsilon=…) → constructor MLPRegressor(hidden_layer_sizes=…, activation=…, solver=…, alpha=…, batch_size=…, learning_rate=…, learning_rate_init=…, power_t=…, max_iter=…, shuffle=…, random_state=…, tol=…, verbose=…, warm_start=…, momentum=…, nesterovs_momentum=…, early_stopping=…, validation_fraction=…, beta_1=…, beta_2=…, epsilon=…, n_iter_no_change=…)
- changed:
method Pipeline.predict(X) → method Pipeline.predict(X, **predict_params) - added:
function make_pipeline(*steps, **kwargs) - added:
function make_union(*transformers, **kwargs)
- added:
export KBinsDiscretizer - added:
export OrdinalEncoder - added:
export PowerTransformer - added:
export power_transform
- removed:
class OneHotEncoder(BaseEstimator, TransformerMixin) - removed:
constructor OneHotEncoder(n_values=…, categorical_features=…, dtype=…, sparse=…, handle_unknown=…) - removed:
method OneHotEncoder.fit(X, y=…) - removed:
method OneHotEncoder.fit_transform(X, y=…) - removed:
method OneHotEncoder.transform(X) - added:
class PowerTransformer(BaseEstimator, TransformerMixin) - added:
constructor KernelCenterer() - added:
constructor PowerTransformer(method=…, standardize=…, copy=…) - added:
export OneHotEncoder - added:
function power_transform(X, method=…, standardize=…, copy=…) - added:
method PowerTransformer.fit(X, y=…) - added:
method PowerTransformer.fit_transform(X, y=…) - added:
method PowerTransformer.inverse_transform(X) - added:
method PowerTransformer.transform(X)
- changed:
constructor BaseLibSVM(impl, kernel, degree, gamma, coef0, tol, C, nu, epsilon, shrinking, probability, cache_size, class_weight, verbose, max_iter, random_state) → constructor BaseLibSVM(kernel, degree, gamma, coef0, tol, C, nu, epsilon, shrinking, probability, cache_size, class_weight, verbose, max_iter, random_state) - changed:
constructor BaseSVC(impl, kernel, degree, gamma, coef0, tol, C, nu, shrinking, probability, cache_size, class_weight, verbose, max_iter, decision_function_shape, random_state) → constructor BaseSVC(kernel, degree, gamma, coef0, tol, C, nu, shrinking, probability, cache_size, class_weight, verbose, max_iter, decision_function_shape, random_state)
- changed:
class OneClassSVM(BaseLibSVM) → class OneClassSVM(BaseLibSVM, OutlierMixin) - added:
method OneClassSVM.score_samples(X)
- added:
class Memory(_joblib.Memory) - added:
class Parallel(_joblib.Parallel) - added:
variable cpu_count - added:
variable delayed - added:
variable effective_n_jobs - added:
variable hash - added:
variable parallel_backend - added:
variable register_parallel_backend
- removed:
function check_fit1d_1feature(name, estimator_orig) - removed:
function check_fit1d_1sample(name, estimator_orig) - removed:
function check_no_fit_attributes_set_in_init(name, Estimator) - changed:
function check_classifiers_train(name, classifier_orig) → function check_classifiers_train(name, classifier_orig, readonly_memmap=…) - changed:
function check_clustering(name, clusterer_orig) → function check_clustering(name, clusterer_orig, readonly_memmap=…) - changed:
function check_estimators_fit_returns_self(name, estimator_orig) → function check_estimators_fit_returns_self(name, estimator_orig, readonly_memmap=…) - changed:
function check_regressors_train(name, regressor_orig) → function check_regressors_train(name, regressor_orig, readonly_memmap=…) - changed:
function check_transformer_general(name, transformer) → function check_transformer_general(name, transformer, readonly_memmap=…) - added:
function check_classifiers_predictions(X, y, name, classifier_orig) - added:
function check_complex_data(name, estimator_orig) - added:
function check_fit1d(name, estimator_orig) - added:
function check_methods_subset_invariance(name, estimator_orig) - added:
function check_no_attributes_set_in_init(name, estimator) - added:
function check_outliers_fit_predict(name, estimator_orig) - added:
function check_outliers_train(name, estimator_orig, readonly_memmap=…) - added:
function check_sample_weights_invariance(name, estimator_orig) - added:
function check_set_params(name, estimator_orig) - added:
function choose_check_classifiers_labels(name, y, y_names) - added:
function pairwise_estimator_convert_X(X, estimator, kernel=…) - added:
variable ALLOW_NAN - added:
variable SUPPORT_STRING
- removed:
function sparse_min_max(X, axis) - added:
function boxcox(x, lmbda) - added:
function nanmedian(a, axis=…) - added:
function nanpercentile(a, q) - added:
variable PY3_OR_LATER
- changed:
function min_max_axis(X, axis) → function min_max_axis(X, axis, ignore_nan=…)
- changed:
function assert_all_finite(X) → function assert_all_finite(X, allow_nan=…) - changed:
function check_X_y(X, y, accept_sparse=…, dtype=…, order=…, copy=…, force_all_finite=…, ensure_2d=…, allow_nd=…, multi_output=…, ensure_min_samples=…, ensure_min_features=…, y_numeric=…, warn_on_dtype=…, estimator=…) → function check_X_y(X, y, accept_sparse=…, accept_large_sparse=…, dtype=…, order=…, copy=…, force_all_finite=…, ensure_2d=…, allow_nd=…, multi_output=…, ensure_min_samples=…, ensure_min_features=…, y_numeric=…, warn_on_dtype=…, estimator=…) - changed:
function check_array(array, accept_sparse=…, dtype=…, order=…, copy=…, force_all_finite=…, ensure_2d=…, allow_nd=…, ensure_min_samples=…, ensure_min_features=…, warn_on_dtype=…, estimator=…) → function check_array(array, accept_sparse=…, accept_large_sparse=…, dtype=…, order=…, copy=…, force_all_finite=…, ensure_2d=…, allow_nd=…, ensure_min_samples=…, ensure_min_features=…, warn_on_dtype=…, estimator=…) - added:
variable LARGE_SPARSE_SUPPORTED