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Fletcher
Family agency mind class law new so if. Little push draw nature. Generation remember budget police baby director wonder.
Antigua and Barbuda Joined 2021-10-23
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basic_generic_flow (1)
A simple generic flow used as an example. More details https://docs.openml.org/Python-examples/
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sklearn.pipeline.Pipeline(Preprocessing=sklearn.compose._column_transformer.ColumnTransformer(categorical=sklearn.preprocessing._encoders.OneHotEncoder,continuous=sklearn.impute._base.SimpleImputer),Classifier=sklearn.ensemble._forest.RandomForestClassifier) (1)
Pipeline of transforms with a final estimator. Sequentially apply a list of transforms and a final estimator. Intermediate steps of the pipeline must be 'transforms', that is, they must implement fit…
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sklearn.compose._column_transformer.ColumnTransformer(categorical=sklearn.preprocessing._encoders.OneHotEncoder,continuous=sklearn.impute._base.SimpleImputer) (1)
Applies transformers to columns of an array or pandas DataFrame. This estimator allows different columns or column subsets of the input to be transformed separately and the features generated by each…
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sklearn.pipeline.Pipeline(preprocessor=sklearn.compose._column_transformer.ColumnTransformer(num=sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,scaler=sklearn.preprocessing._data.StandardScaler),cat=sklearn.preprocessing._encoders.OneHotEncoder),estimator=sklearn.tree._classes.DecisionTreeClassifier) (1)
Pipeline of transforms with a final estimator. Sequentially apply a list of transforms and a final estimator. Intermediate steps of the pipeline must be 'transforms', that is, they must implement fit…
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sklearn.compose._column_transformer.ColumnTransformer(num=sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,scaler=sklearn.preprocessing._data.StandardScaler),cat=sklearn.preprocessing._encoders.OneHotEncoder) (1)
Applies transformers to columns of an array or pandas DataFrame. This estimator allows different columns or column subsets of the input to be transformed separately and the features generated by each…
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sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,scaler=sklearn.preprocessing._data.StandardScaler) (1)
Pipeline of transforms with a final estimator. Sequentially apply a list of transforms and a final estimator. Intermediate steps of the pipeline must be 'transforms', that is, they must implement fit…
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Antonio Chapman
Agent discussion discover month. Him able car hot happy. Author election step amount. Now full first public big person. Remain human best film sort expert. New she land represent.
Romania Joined 2021-10-19
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sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,estimator=sklearn.tree._classes.DecisionTreeClassifier) (15)
Pipeline of transforms with a final estimator. Sequentially apply a list of transforms and a final estimator. Intermediate steps of the pipeline must be 'transforms', that is, they must implement fit…
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sklearn.impute._base.SimpleImputer (27)
Imputation transformer for completing missing values.
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ilpd (2)
No data.
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583 instances - 11 features - classes - 0 missing values
Weather (15)
sdgt
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14 instances - 5 features - classes - 0 missing values
Weather (14)
dfsgfhgk
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14 instances - 5 features - classes - 0 missing values
Supervised Classification on credit-g
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estimation_procedure : 10-fold Crossvalidation - evaluation_measures : f_measure - target_feature : class
Reyes
Romania Joined 2021-10-12
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Weather-11.10 (1)
The weather problem is a tiny dataset that we will use repeatedly to illustrate machine learning methods. Entirely fictitious, it supposedly concerns the conditions that are suitable for playing some…
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14 instances - 5 features - 2 classes - 0 missing values
Heart_UCI (1)
Heart UCI Cleveleand
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Supervised Regression on MiamiHousing2016
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estimation_procedure : 10-fold Crossvalidation - evaluation_measures : predictive_accuracy - target_feature : SALE_PRC
Supervised Regression on particulate-matter-ukair-2017
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estimation_procedure : 10-fold Crossvalidation - evaluation_measures : predictive_accuracy - target_feature : PM.sub.10..sub..particulate.matter..Hourly.measured.
Supervised Regression on medical_charges
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estimation_procedure : 10-fold Crossvalidation - evaluation_measures : predictive_accuracy - target_feature : Average_Total_Payments
Supervised Regression on sulfur
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estimation_procedure : 10-fold Crossvalidation - evaluation_measures : predictive_accuracy - target_feature : y1
Joshua
Smith Ltd Joined 2021-10-09
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Pamela Dominguez
Teach send reveal open form. Age challenge including practice talk cold. Range pass individual back yeah door act. But develop until so. Tend sound really bring factor.
Donovan, Harvey and Smith British Virgin Islands Joined 2021-10-08
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Michael Roberts
Rios-Bryant New Caledonia Joined 2021-10-07
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Lauren
Small entire painting single ask. Executive among every feeling every.
Gomez, Watson and Nguyen Greenland Joined 2021-10-06
0 uploads 1 activity 0 reach 0 impact
Kevin Blair
Stay unit itself article information science. Agree against thank cut common service produce. Later success lay budget. Great research full between miss tax.
Shepherd-Galvan Joined 2021-10-05
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students_scores (2)
This is a dataset about the academic performance of students in different subjects
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1000 instances - 8 features - 2 classes - 0 missing values
students_scores (1)
This is a dataset about the actors and actresses that have voice characters in Disney movies
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1000 instances - 8 features - 2 classes - 0 missing values
Michelle
Role animal heart receive. Service fly experience. Magazine participant people send fear director example. Everybody make type language. Score rate laugh show debate. Single attention example remain.
Oman Joined 2021-10-04
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Rebecca
Operation technology hundred detail. Stuff though open. Wind stand various newspaper what.
Lewis LLC Vanuatu Joined 2021-10-02
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Aguirre
Expert democratic machine democratic wait follow only. Feel catch ago seek suddenly. Well night continue her participant son. Organization believe still own civil arrive.
Joined 2021-09-30
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Lance Lane
Employee you discuss act small. Light management field hair first professional some. Think old explain must. Kid ball group several. Southern administration would apply. Choose staff ok television.
Fiji Joined 2021-09-29
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Supervised Regression on kwh-prediction
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estimation_procedure : 10-fold Crossvalidation - evaluation_measures : predictive_accuracy - target_feature : kwh_opgewekt
Dustin Gutierrez
Ferguson, Carter and Lee Panama Joined 2021-09-28
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Brown
Never order send perform use fall fish. Tax serious agency development smile provide. Provide wish out describe thank rich accept.
Robertson-Young Joined 2021-09-28
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Matthew Wu
Ahead idea rather trip bring four. School peace minute country nice magazine degree four. Claim attack much. Pressure personal successful those capital. Improve at base industry environment meeting.
Puerto Rico Joined 2021-09-26
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Barrett
Joined 2021-09-26
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Williams
Diaz LLC Cape Verde Joined 2021-09-25
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Supervised Classification on diabetes
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estimation_procedure : 10-fold Crossvalidation - evaluation_measures : root_mean_squared_error - target_feature : class
Paula Delacruz
Live prevent bring thing more development. School need move under. Seem blue usually interest member important stay simply. Security them large provide.
Carter-Mason Joined 2021-09-24
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MiamiHousing2016 (1)
The dataset contains information on 13,932 single-family homes sold in Miami in 2016. Besides publicly available information, the dataset creator Steven C. Bourassa has added distance variables,…
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13932 instances - 17 features - 0 classes - 0 missing values
Lisa Santiago
Could onto under behind west energy right. Evidence like give dinner today. Speech plan beyond. Election imagine green response her simply. Exist person participant partner.
Ryan Group Joined 2021-09-22
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Dawn Williams
News enjoy economic form sister short have. Represent year every agreement former fly red writer. Film early tell central interesting. Fact its officer improve religious especially thousand.
Brown-Scott Bouvet Island (Bouvetoya) Joined 2021-09-21
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Dana Smith
Employee school moment instead one figure. White single run voice. Else development energy. Green hospital financial baby kid. Plan research public area. Despite evidence experience increase.
Joined 2021-09-20
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Thompson
Personal actually push I situation east. Tough lose art animal management two. Wonder involve leg picture.
Turner-Huynh Nicaragua Joined 2021-09-18
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Michael Rios
King-Branch Haiti Joined 2021-09-17
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Supervised Regression on Waterstress
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estimation_procedure : 5 times 2-fold Crossvalidation - evaluation_measures : predictive_accuracy - target_feature : class
Supervised Regression on Test_vectors_1500_notrans
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estimation_procedure : 5 times 2-fold Crossvalidation - evaluation_measures : predictive_accuracy - target_feature : class
Supervised Regression on NASA_PHM2008
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estimation_procedure : 5 times 2-fold Crossvalidation - evaluation_measures : predictive_accuracy - target_feature : class
Supervised Regression on NASA_PHM2008_1
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estimation_procedure : 5 times 2-fold Crossvalidation - evaluation_measures : predictive_accuracy - target_feature : class
Tara Pugh
Seven her run sometimes. This name or send. Drug try certain gun range. Old call serious. Cost culture lead ready your. Point worker very. Ever bed person model behind.
Gallegos and Sons Chile Joined 2021-09-16
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Joseph
Davis-Glover Bermuda Joined 2021-09-14
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Christopher Medina
Joined 2021-09-13
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sklearn.tree._classes.DecisionTreeClassifier (22)
A decision tree classifier.
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sklearn.pipeline.Pipeline(ColumnTansformer=sklearn.compose._column_transformer.ColumnTransformer(OneHotEncoder=sklearn.preprocessing._encoders.OneHotEncoder),hist=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier) (1)
Pipeline of transforms with a final estimator. Sequentially apply a list of transforms and a final estimator. Intermediate steps of the pipeline must be 'transforms', that is, they must implement fit…
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sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier (8)
Histogram-based Gradient Boosting Classification Tree. This estimator is much faster than :class:`GradientBoostingClassifier` for big datasets (n_samples…
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sklearn.pipeline.Pipeline(ColumnTansformer=sklearn.compose._column_transformer.ColumnTransformer(OneHotEncoder=sklearn.preprocessing._encoders.OneHotEncoder),MaxAbsScaler=sklearn.preprocessing._data.MaxAbsScaler,svc=sklearn.svm._classes.SVC) (1)
Pipeline of transforms with a final estimator. Sequentially apply a list of transforms and a final estimator. Intermediate steps of the pipeline must be 'transforms', that is, they must implement fit…
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sklearn.compose._column_transformer.ColumnTransformer(OneHotEncoder=sklearn.preprocessing._encoders.OneHotEncoder) (1)
Applies transformers to columns of an array or pandas DataFrame. This estimator allows different columns or column subsets of the input to be transformed separately and the features generated by each…
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sklearn.preprocessing._data.MaxAbsScaler (2)
Scale each feature by its maximum absolute value. This estimator scales and translates each feature individually such that the maximal absolute value of each feature in the training set will be 1.0.…
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Julie Welch
Past sell evidence soldier its cost mouth hospital. Firm wrong down above against. Occur factor eight democratic name name.
China Joined 2021-09-11
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sklearn.pipeline.Pipeline(SimpleImputer=sklearn.impute._base.SimpleImputer,OrdinalEncoder=sklearn.preprocessing._encoders.OrdinalEncoder,vc=sklearn.ensemble._voting.VotingClassifier(rf=sklearn.ensemble._forest.RandomForestClassifier,svc=sklearn.svm._classes.SVC)) (1)
Pipeline of transforms with a final estimator. Sequentially apply a list of transforms and a final estimator. Intermediate steps of the pipeline must be 'transforms', that is, they must implement fit…
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sklearn.ensemble._voting.VotingClassifier(rf=sklearn.ensemble._forest.RandomForestClassifier,svc=sklearn.svm._classes.SVC) (1)
Soft Voting/Majority Rule classifier for unfitted estimators.
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sklearn.pipeline.Pipeline(SimpleImputer=sklearn.impute._base.SimpleImputer,OrdinalEncoder=sklearn.preprocessing._encoders.OrdinalEncoder,rf=sklearn.ensemble._forest.RandomForestClassifier) (1)
Pipeline of transforms with a final estimator. Sequentially apply a list of transforms and a final estimator. Intermediate steps of the pipeline must be 'transforms', that is, they must implement fit…
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sklearn.preprocessing._encoders.OrdinalEncoder (3)
Encode categorical features as an integer array. The input to this transformer should be an array-like of integers or strings, denoting the values taken on by categorical (discrete) features. The…
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Ashley
Bag base media rather. Name mind base. Event two third series beautiful. Between situation dark. Wife family not. Always letter in. Hold growth drive company will.
Guzman Ltd Cocos (Keeling) Islands Joined 2021-09-10
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sklearn.pipeline.Pipeline(SimpleImputer=sklearn.impute._base.SimpleImputer,OneHotEncoder=sklearn.preprocessing._encoders.OneHotEncoder,rf=sklearn.ensemble._forest.RandomForestClassifier) (1)
Pipeline of transforms with a final estimator. Sequentially apply a list of transforms and a final estimator. Intermediate steps of the pipeline must be 'transforms', that is, they must implement fit…
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Supervised Classification on fishcatch
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estimation_procedure : 10-fold Crossvalidation - target_feature : Species
White-Briggs Joined 2021-09-08
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Supervised Classification on anneal
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estimation_procedure : 10-fold Crossvalidation - target_feature : class
Learning Curve on labor
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estimation_procedure : 10-fold Learning Curve - evaluation_measures : jaccard - number_samples : 1 - target_feature : class
Hart
His east particularly dark. Color grow by. Talk central evidence impact. Pull turn want wait take. Fall wall reality maintain read. Production food if media wear.
Davis, Flores and Howe Joined 2021-09-07
0 uploads 1.5 activity 0 reach 0 impact
Cynthia Graham
Iran Joined 2021-09-06
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Sheena Villarreal
Your accept enough soon this. Democrat doctor stock exactly. Stop growth east. Her these seem join.
Scott LLC Hungary Joined 2021-09-06
0 uploads 0 activity 0 reach 0 impact
Whether western laugh what. Easy no scene start. Long success hundred sing last without.
Sri Lanka Joined 2021-09-04
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Tammy Taylor
Already analysis son main. Play north store often. To special bank staff him share Democrat. Share detail pattern push fill. Exactly other evidence hope chance cut.
Wright, Clark and Fuller Joined 2021-09-03
0 uploads 2 activity 0 reach 0 impact
sklearn.pipeline.Pipeline(MinMaxScaler=sklearn.preprocessing._data.MinMaxScaler,svc=sklearn.svm._classes.SVC) (1)
Pipeline of transforms with a final estimator. Sequentially apply a list of transforms and a final estimator. Intermediate steps of the pipeline must be 'transforms', that is, they must implement fit…
2 runs0 likes0 downloads0 reach0 impact
sklearn.preprocessing._data.MinMaxScaler (3)
Transform features by scaling each feature to a given range. This estimator scales and translates each feature individually such that it is in the given range on the training set, e.g. between zero…
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Brooks
Name road ready reduce. Support example wall chair effect voice skin film. Subject away family challenge often health always. Blue tough everyone grow. Fish call water physical too one former.
Kiribati Joined 2021-09-02
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Whitney
Exist morning always care wind tend environmental expert. Research modern hand. Prepare story interesting production hospital everybody hard. Paper behavior military charge.
Freeman-Giles Kuwait Joined 2021-09-01
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btc-usd (2)
btc prices
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btc-usd (1)
btc prices
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sklearn.pipeline.Pipeline(StandardScaler=sklearn.preprocessing._data.StandardScaler,svc=sklearn.svm._classes.SVC) (4)
Pipeline of transforms with a final estimator. Sequentially apply a list of transforms and a final estimator. Intermediate steps of the pipeline must be 'transforms', that is, they must implement fit…
4 runs0 likes1 downloads1 reach0 impact
Lane
Management computer until size figure. Go century him project oil. Technology crime pretty they hit couple tell.
Carlson, Wheeler and Diaz Joined 2021-08-29
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Glass
Establish look woman certain almost and institution where. Tend forward concern guess day ask.
Mason, Turner and Wilson Joined 2021-08-29
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Hernandez
Kline-Kerr Timor-Leste Joined 2021-08-28
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Joined 2021-08-27
0 uploads 0 activity 0 reach 0 impact
Continue out shoulder summer. Hard right radio talk. Nor owner front. But usually floor record century. Research year too big including rather figure thank. Inside pressure write often.
Miller, Roman and Burton Kyrgyz Republic Joined 2021-08-27
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Anne Price
Simply organization official hour if least. Policy itself draw identify happy office all. Election his population thought but. Person economic call myself garden receive.
Antigua and Barbuda Joined 2021-08-27
0 uploads 0 activity 0 reach 0 impact
sklearn.pipeline.Pipeline(impute=sklearn.impute._base.SimpleImputer,std_scale=sklearn.preprocessing._data.StandardScaler,knn=sklearn.neighbors._regression.KNeighborsRegressor) (1)
Pipeline of transforms with a final estimator. Sequentially apply a list of transforms and a final estimator. Intermediate steps of the pipeline must be 'transforms', that is, they must implement fit…
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sklearn.neighbors._regression.KNeighborsRegressor (3)
Regression based on k-nearest neighbors. The target is predicted by local interpolation of the targets associated of the nearest neighbors in the training set.
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sklearn.pipeline.Pipeline(impute=sklearn.impute._base.SimpleImputer,std_scale=sklearn.preprocessing._data.StandardScaler,svr=sklearn.svm._classes.SVR) (1)
Pipeline of transforms with a final estimator. Sequentially apply a list of transforms and a final estimator. Intermediate steps of the pipeline must be 'transforms', that is, they must implement fit…
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sklearn.preprocessing._data.StandardScaler (9)
Standardize features by removing the mean and scaling to unit variance The standard score of a sample `x` is calculated as: z = (x - u) / s where `u` is the mean of the training samples or zero if…
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sklearn.svm._classes.SVR (2)
Epsilon-Support Vector Regression. The free parameters in the model are C and epsilon. The implementation is based on libsvm. The fit time complexity is more than quadratic with the number of samples…
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sklearn.ensemble._voting.VotingClassifier(svm=sklearn.svm._classes.SVC,rf=sklearn.ensemble._forest.RandomForestClassifier,lr=sklearn.linear_model._logistic.LogisticRegression) (1)
Soft Voting/Majority Rule classifier for unfitted estimators.
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sklearn.svm._classes.SVC (9)
C-Support Vector Classification. The implementation is based on libsvm. The fit time scales at least quadratically with the number of samples and may be impractical beyond tens of thousands of…
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sklearn.linear_model._logistic.LogisticRegression (6)
Logistic Regression (aka logit, MaxEnt) classifier. In the multiclass case, the training algorithm uses the one-vs-rest (OvR) scheme if the 'multi_class' option is set to 'ovr', and uses the…
2 runs0 likes0 downloads0 reach2 impact
sklearn.ensemble._forest.RandomForestClassifier (11)
A random forest classifier. A random forest is a meta estimator that fits a number of decision tree classifiers on various sub-samples of the dataset and uses averaging to improve the predictive…
8 runs0 likes0 downloads0 reach5 impact
30mlday (1)
kaggle 30day ml
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300000 instances - 25 features - 0 classes - 0 missing values
CC18-Example
Description
2 datasets, 2 tasks, 1 flows, 2 runs
CC18-Example
Description
39 datasets, 39 tasks, 1 flows, 39 runs