Fix defaultdict behavior on NumericalEncoder #21
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* fix bug when no elements to iterator on * remove useless space
* add failing test for categorie * - add a function that can replace categorical columns by object columns - recognize 'category' as a CAT type of variable * ajoute de get ride of categories modifications des transfo numericalencoder et targetencoder ajout d un test de guess_type_of_variables * - add a get_rid_of_categories in the fit_transform of targetencoder - add test of targetencoder with categorical dtype - add test of numericalencoder with categorical dtype * modif de test_guesss_type_of_variable * ajout d'un test permettant de vérifier que le numerical encoder ne transforme pas les colonnes catégorielles ayant des int en colonnes numériques. pour l'instant, le test fail * modification du code pour que le numericalencoder et le targetencoder fonctionnent correctement ajout de tests * modifs prenant en compte les comments de la pull request * remaining changes for the pull request * clean commit
* Block Search + other (#2) * add make_pipeline function (works like sklearn) * fix type "_if_fitted" -> "_already_fitted" * * add handling of columns_to_encode == "--object--" in target encoder * corresponding test * add Numerical encoder test for "columns_to_encode == '--object--' " * expose command argument parser outside, to be able to add new arguments. * change WordVectorizer in char mod distributions + fix bug in HyperRangeBetaInt * change default behavior : encode "columns_to_encode == '--object--' " * remove 'bug' (double return) * allow text preprocessors to concat their inputs * add 'RandomTrainTestCv' and 'IndexTrainCv' cv-like object. * same api as a regular cv object ... * ... but only one split * add 'use_for_block_search' attribute + filter models based on that * * add block search iterator * automl config : models_to_keep_block_search * fix typo in test * ignore Warning in test * move 'function_has_named_argument' from .transformers.model_wrapper to .tools.helper_functions * cleanning * dispatch and split the groups variable to the estimator * add groups to methods + dispatch it to estimators within the pipeline * test on cross validation and pipeline to check the passing of groups * remove useless import * remove useless * fix X -> lastX * debug help * fix after merge * make sur benchmark can be computed * input np.inf as well as np.nan * spaces * don't split and tokenize if not needed * new tests auto-ml, when only numerical values * allow scoring to return multiple values * allow cross_validation to be in Parallel # Conflicts: # aikit/cross_validation.py * add a custom CV for groups * * froze init param * allow additionnal function to be computed * read additionnal results * allow guiding to be done on an "addtionnal metric" * typo * add name of excel print * test if name of columns has change
* remove config.json * fix loading * remove nltk addtional path
* accelerate code using map and dict * accelerate concatenation code * Update categories
* fix seed * new test CdfScaler
* * new helpers function (merge node and subbranch search) * fix ordering in graph from edges * * generalize the notion of model graph * change name representation * Block Search + other (#2) * add make_pipeline function (works like sklearn) * fix type "_if_fitted" -> "_already_fitted" * * add handling of columns_to_encode == "--object--" in target encoder * corresponding test * add Numerical encoder test for "columns_to_encode == '--object--' " * expose command argument parser outside, to be able to add new arguments. * change WordVectorizer in char mod distributions + fix bug in HyperRangeBetaInt * change default behavior : encode "columns_to_encode == '--object--' " * remove 'bug' (double return) * allow text preprocessors to concat their inputs * add 'RandomTrainTestCv' and 'IndexTrainCv' cv-like object. * same api as a regular cv object ... * ... but only one split * add 'use_for_block_search' attribute + filter models based on that * * add block search iterator * automl config : models_to_keep_block_search * fix typo in test * ignore Warning in test * fix type : TransformToBlockManager * add number of output utils function * spaces * new tests with impossible graphs * fix merged * fix notebook error * add list test * remove useless import * spaces * fix docstring * merge 2 loops * remove duplicate edge
* add a few ploting functions * add assert
gfournier
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Feb 28, 2020
* fix bug when type_of_problem is setted * add default * add specific test
gfournier
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Feb 28, 2020
* bump version to 0.1.3 * bump version to 0.1.4-dev * massive black reformating (#18) * fix bug when type_of_problem is setted (#21) * fix bug when type_of_problem is setted * add default * add specific test * Fix numericalencoder (#22) * fix NumericalEncoder with default values * fix NumericalEncoder with default values * Fix doc (#26) * ignore .bat file to create doc * fix doc * comment in english * clean test * requirements pandas >= 0.23 (#27) * node -> nodes (was deprecated and is now absent) (#31) * Add test picklable (#23) * test numerical encoder is picklable * test numerical encoder is picklable * test target encoder is picklable * black * black * remove warning printing * add test : unpickled object behave like original object * improve auto ml doc (#30) * re-index 'fit_params' that are indexable * change version 0.1.5 * conversion model to json (#36) * v0.1.6-dev * add conversion model to json : 'param_from_sklearn_model' + corresponding tests * add new numpy type to be cast to python type * test if object can be json serialized * refactoring of columns selection (#29) * add conversion model to json : 'param_from_sklearn_model' + corresponding tests * change wrapper, 'drop_used_columns' and 'drop_unused_columns' * temp : remove useless attribute * temp : fix test * allow selector to select of type of variable among TypeOfVariables.CAT / TEXT / NUM * change default for numerical encoder * change test * temp : new test * renamming * comments * clean docstring * change text models * change 'base' models * change corresponding tests * add numpy array support * fix tests * fix test * fix random_forest_addins columns_to_use * fix Targetencoder * fix special case when no column to pass to the model * typo * fix get_feature_names * allow not to raise when shape between fit and transform differs * corresponding tests * cleanning * fix doc + default * rename * fix registration * black reformat * clean * add helper method * temp add fitting test * clean * add test : try to fit model * add custom default hyper-parameters * fix inf * clean * add test not inf CdfScaler * cap number of component to nb of rows * fix seed by default * clean * make CdfScaler to very small, almost equal values * test very close and very small values * cleanning * divers * add min_count param * more data in test * * remove cast of string that can be parsed * corresponding test * change version 1.0.0 * dev version 1.0.1-dev * change version 0.2.0 * dev 0.2.1-dev
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