resources/ddl/define-all.deprecated.hive

drop temporary function if exists perceptron;
create temporary function perceptron as 'hivemall.classifier.PerceptronUDTF';

drop temporary function if exists adagrad_rda;
create temporary function adagrad_rda as 'hivemall.classifier.AdaGradRDAUDTF';

drop temporary function if exists cosine_sim;
create temporary function cosine_sim as 'hivemall.knn.similarity.CosineSimilarityUDF';

drop temporary function if exists jaccard;
create temporary function jaccard as 'hivemall.knn.similarity.JaccardIndexUDF';

drop temporary function if exists wvoted_avg;
create temporary function wvoted_avg as 'hivemall.ensemble.bagging.WeightVotedAvgUDAF';

drop temporary function if exists sortByFeature;
create temporary function sortByFeature as 'hivemall.ftvec.SortByFeatureUDF';

drop temporary function if exists train_logregr;
create temporary function train_logregr as 'hivemall.regression.LogressUDTF';

drop temporary function if exists pa1_regress;
create temporary function pa1_regress as 'hivemall.regression.PassiveAggressiveRegressionUDTF';

drop temporary function if exists pa1a_regress;
create temporary function pa1a_regress as 'hivemall.regression.PassiveAggressiveRegressionUDTF$PA1a';

drop temporary function if exists pa2_regress;
create temporary function pa2_regress as 'hivemall.regression.PassiveAggressiveRegressionUDTF$PA2';

drop temporary function if exists pa2a_regress;
create temporary function pa2a_regress as 'hivemall.regression.PassiveAggressiveRegressionUDTF$PA2a';

drop temporary function if exists arow_regress;
create temporary function arow_regress as 'hivemall.regression.AROWRegressionUDTF';

drop temporary function if exists arowe_regress;
create temporary function arowe_regress as 'hivemall.regression.AROWRegressionUDTF$AROWe';

drop temporary function if exists arowe2_regress;
create temporary function arowe2_regress as 'hivemall.regression.AROWRegressionUDTF$AROWe2';

drop temporary function if exists adagrad_regr;
create temporary function adagrad_regr as 'hivemall.regression.AdaGradUDTF';

drop temporary function if exists adagrad;
create temporary function adagrad as 'hivemall.regression.AdaGradUDTF';

drop temporary function if exists train_adadelta;
create temporary function train_adadelta as 'hivemall.regression.AdaDeltaUDTF';

drop temporary function if exists adadelta;
create temporary function adadelta as 'hivemall.regression.AdaDeltaUDTF';

drop temporary function if exists collect_all;
create temporary function collect_all as 'hivemall.tools.array.CollectAllUDAF';

drop temporary function if exists train_gbt_classifier;
create temporary function train_gbt_classifier as 'hivemall.smile.classification.GradientTreeBoostingClassifierUDTF';

drop temporary function if exists train_arowh;
create temporary function train_arowh as 'hivemall.classifier.AROWClassifierUDTF$AROWh';

drop temporary function if exists normalize;
create temporary function normalize as 'hivemall.ftvec.scaling.L2NormalizationUDF';

drop temporary function if exists train_adagrad;
create temporary function train_adagrad as 'hivemall.regression.AdaGradUDTF';

drop temporary function if exists rescale_fv;
create temporary function rescale_fv as 'hivemall.ftvec.scaling.RescaleUDF';

drop temporary function if exists addBias;
create temporary function addBias as 'hivemall.ftvec.AddBiasUDF';

drop temporary function if exists sha1;
create temporary function sha1 as 'hivemall.ftvec.hashing.Sha1UDF';

drop temporary function if exists map_index;
create temporary function map_index as 'hivemall.tools.map.MapGetUDF';