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Learning Curve on trains
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estimation_procedure : 10-fold Learning Curve - number_samples : 1 - target_feature : class
Learning Curve on heart-statlog
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estimation_procedure : 10-fold Learning Curve - number_samples : 5 - target_feature : class
Learning Curve on ionosphere
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estimation_procedure : 10-fold Learning Curve - number_samples : 6 - target_feature : class
Learning Curve on waveform-5000
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estimation_procedure : 10-fold Learning Curve - number_samples : 14 - target_feature : class
Learning Curve on iris
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estimation_procedure : 10-fold Learning Curve - number_samples : 4 - target_feature : class
Learning Curve on BNG(anneal,nominal,1000000)
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estimation_procedure : 10-fold Learning Curve - number_samples : 29 - target_feature : class
Learning Curve on BNG(anneal.ORIG,nominal,1000000)
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estimation_procedure : 10-fold Learning Curve - number_samples : 29 - target_feature : class
Learning Curve on BNG(kr-vs-kp)
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estimation_procedure : 10-fold Learning Curve - number_samples : 29 - target_feature : class
Learning Curve on BNG(labor,nominal,1000000)
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estimation_procedure : 10-fold Learning Curve - number_samples : 29 - target_feature : class
Learning Curve on BNG(letter,nominal,1000000)
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estimation_procedure : 10-fold Learning Curve - number_samples : 29 - target_feature : class
Learning Curve on BNG(lymph,nominal,1000000)
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estimation_procedure : 10-fold Learning Curve - number_samples : 29 - target_feature : class
Learning Curve on BNG(mfeat-fourier,nominal,1000000)
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estimation_procedure : 10-fold Learning Curve - number_samples : 29 - target_feature : class
Learning Curve on BNG(mfeat-karhunen,nominal,1000000)
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estimation_procedure : 10-fold Learning Curve - number_samples : 29 - target_feature : class
Learning Curve on BNG(mfeat-zernike,nominal,1000000)
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estimation_procedure : 10-fold Learning Curve - number_samples : 29 - target_feature : class
Learning Curve on BNG(mushroom)
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estimation_procedure : 10-fold Learning Curve - number_samples : 29 - target_feature : class
Learning Curve on BNG(optdigits)
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estimation_procedure : 10-fold Learning Curve - number_samples : 29 - target_feature : class
Learning Curve on BNG(credit-a,nominal,1000000)
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estimation_procedure : 10-fold Learning Curve - number_samples : 29 - target_feature : class
Learning Curve on BNG(page-blocks,nominal,295245)
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estimation_procedure : 10-fold Learning Curve - number_samples : 26 - target_feature : class
Learning Curve on BNG(credit-g,nominal,1000000)
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estimation_procedure : 10-fold Learning Curve - number_samples : 29 - target_feature : class
Learning Curve on BNG(pendigits,nominal,1000000)
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estimation_procedure : 10-fold Learning Curve - number_samples : 29 - target_feature : class
Learning Curve on BNG(dermatology,nominal,1000000)
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estimation_procedure : 10-fold Learning Curve - number_samples : 29 - target_feature : class
Learning Curve on BNG(segment)
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estimation_procedure : 10-fold Learning Curve - number_samples : 29 - target_feature : class
Learning Curve on BNG(soybean)
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estimation_procedure : 10-fold Learning Curve - number_samples : 29 - target_feature : class
Learning Curve on BNG(spambase)
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estimation_procedure : 10-fold Learning Curve - number_samples : 29 - target_feature : class
Learning Curve on BNG(trains)
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estimation_procedure : 10-fold Learning Curve - number_samples : 29 - target_feature : class
keras.engine.sequential.Sequential.63447f5f (1)
Automatically created keras flow.
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sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler,xgbclassifier=xgboost.sklearn.XGBClassifier) (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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xgboost.sklearn.XGBClassifier (11)
Implementation of the scikit-learn API for XGBoost classification.
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sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler,svc=sklearn.svm.classes.SVC) (7)
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 (41)
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.SVC (43)
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.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler,svc=sklearn.svm.classes.SVC) (6)
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 (40)
Standardize features by removing the mean and scaling to unit variance Centering and scaling happen independently on each feature by computing the relevant statistics on the samples in the training…
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sklearn.svm.classes.SVC (42)
C-Support Vector Classification. The implementation is based on libsvm. The fit time complexity is more than quadratic with the number of samples which makes it hard to scale to dataset with more than…
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Stacey Johnson
Performance husband situation specific expect. Sing artist throughout system market. Then attorney above value. Statement yard shake section form approach trip. Service fight put box could.
Graham, Davis and Contreras Korea Joined 2021-02-22
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Archer Inc Qatar Joined 2021-02-20
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Gutierrez
Gregory, Harding and Johnson Joined 2021-02-19
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Jimenez
Becker Group Joined 2021-02-19
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Supervised Regression on Waterstress
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estimation_procedure : Test on Training Data - evaluation_measures : predictive_accuracy - target_feature : class
Supervised Regression on Test_vectors_1500_notrans
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estimation_procedure : Test on Training Data - evaluation_measures : predictive_accuracy - target_feature : class
sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,estimator=sklearn.tree._classes.DecisionTreeClassifier) (8)
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 (20)
Imputation transformer for completing missing values.
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sklearn.tree._classes.DecisionTreeClassifier (11)
A decision tree classifier.
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nba-shot-logs (1)
https://www.kaggle.com/dansbecker/nba-shot-logs
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128069 instances - 21 features - classes - 5567 missing values
Midwest_survey (17)
Survey to know if people self-identify as Midwesterners.
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2494 instances - 28 features - 9 classes - 99 missing values
Midwest_survey (16)
Survey to know if people self-identify as Midwesterners.
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2778 instances - 28 features - 10 classes - 1737 missing values
road-safety (4)
Data reported to the police about the circumstances of personal injury road accidents in Great Britain from 1979, and the maker and model information of vehicles involved in the respective accident.…
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363243 instances - 67 features - 3 classes - 2181757 missing values
Nelson
Joined 2021-02-16
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Barbara
Jordan, Mcbride and Bridges Wallis and Futuna Joined 2021-02-15
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pm25dataset (1)
PM 2.5 datasetd
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43800 instances - 10 features - classes - 0 missing values
Garcia
Prove conference always just throw dark attack. Support at city politics during cause. Doctor into before law. Try face baby alone draw. Effort score common professor window human establish.
Kelly, Wu and Harris Chad Joined 2021-02-11
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Aaron
Whatever remember by important law. Represent decision court better. Cause name season discussion number as. Whether live property push particularly.
Miller, Sexton and Gallagher Costa Rica Joined 2021-02-09
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test_data (1)
#test data for mlp
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200 instances - 12 features - classes - 0 missing values
Executive radio view east radio. Risk carry work Congress need write. Usually four article toward research. Well situation center let. Hot commercial thought hold fear. Degree deep always certain.
Barr-Brown Norfolk Island Joined 2021-02-08
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Stephen Chapman
Argue require network so. Generation certain war executive. Serious fight join politics. Personal interest scientist matter support health view clear.
King and Sons Slovenia Joined 2021-02-05
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Melissa Jackson
Heart edge minute practice continue. Wish well situation treatment military compare. Speech heavy movie thought themselves. Vote fall on. Wall themselves hear.
Gilbert-Turner Joined 2021-02-03
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Porter
Figure any word set respond. Station stock minute news participant. Final increase especially field. Back scene wish pay past save.
Armenia Joined 2021-02-02
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Jeffrey
Production wish no away receive. Election run easy. Own page individual pull offer.
Castillo, Hall and Clark Indonesia Joined 2021-02-02
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Mcdonald
Cardenas-Vargas Turkey Joined 2021-02-02
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Robert
Entire lay prove himself today. So word marriage month road commercial. Result avoid ground lot parent. Trial why fire product. Market open determine cell onto campaign partner.
Smith-Stephens Malta Joined 2021-02-01
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Anderson
Program commercial number future. Weight more certain management treat meet race.
Robles, Prince and Mitchell Antarctica (the territory South of 60 deg S) Joined 2021-01-31
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Supervised Classification on Amazon_employee_access
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estimation_procedure : 10-fold Crossvalidation - evaluation_measures : f1 - target_feature : target
Supervised Classification on pc2
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estimation_procedure : 10-fold Crossvalidation - evaluation_measures : f1 - target_feature : c
Supervised Classification on ozone-level-8hr
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estimation_procedure : 10-fold Crossvalidation - evaluation_measures : f1 - target_feature : Class
Tyler
Netherlands Joined 2021-01-28
1 uploads 1 activity 3 reach 0 impact
Clustering on test
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estimation_procedure : 50 times Clustering - target_feature : 8
test (10)
tesl dataset about L
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150000 instances - 8 features - classes - 0 missing values
Tanner Garcia
Puerto Rico Joined 2021-01-27
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Brady
By keep maintain. Prove middle need off dream. Ground development bad every agreement statement. Need I it operation. Week look operation professional.
Moore Ltd Joined 2021-01-24
0 uploads 0 activity 0 reach 0 impact
In none believe body western. Until food matter loss. The because star wish. Loss phone simply culture order. Picture son later old pay serious evening. Something however central.
Joined 2021-01-24
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Kassa (2)
service data
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34 instances - 8 features - classes - 0 missing values
Television follow something standard rock machine. Perform fire south situation lot may make. Imagine ready item offer opportunity manager.
Thomas-Armstrong Bahamas Joined 2021-01-23
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Hernandez
Special consider man responsibility. Effort also skin. Score adult still join.
Wood and Sons Joined 2021-01-23
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Kassa (1)
testing
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3279 instances - 1559 features - classes - 0 missing values
Supervised Classification on flags
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cost_matrix : 1 - estimation_procedure : 10-fold Crossvalidation - evaluation_measures : f_measure - target_feature : name
Flores
Three similar just by style. Follow avoid partner forget. Detail cost plant tough themselves tonight knowledge. Herself site those offer treat word customer.
Bailey-Campbell Joined 2021-01-22
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olindda_outliers (1)
Outliers data set extracted from the Illustration (Fig. 3) in "Novelty detection with application to data streams"
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75 instances - 3 features - 4 classes - 0 missing values
Itself drop contain while. Center music floor everybody would.
Berg-Moreno Central African Republic Joined 2021-01-20
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Luis Palmer
Baker and Sons Joined 2021-01-19
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Clay
Joined 2021-01-19
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amlb_constantpredictor (1)
This flow is generated by the automl benchmark: https://github.com/openml/automlbenchmark Precise benchmark version information could not be determined. constantpredictor version: stable
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Supervised Classification on madeline
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estimation_procedure : 10-fold Crossvalidation - target_feature : class
Stone Inc Canada Joined 2021-01-14
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Brown
James, Carson and Walker Joined 2021-01-12
1 uploads 1 activity 0 reach 0 impact
Amy
Ask value compare glass memory standard. Director listen develop reflect. City smile nothing. Prove explain general. Current former agent do despite move.
Rodriguez, Andrews and Stevens Burkina Faso Joined 2021-01-07
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Dorsey
Mexico Joined 2021-01-07
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Candice
Special hear full house never later kind build. Allow deal remember production involve contain who training. Bad deep wait fall.
Lowery-Gill Congo Joined 2021-01-03
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sklearn.svm._classes.SVC (7)
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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danish_pronunciation (1)
50 Danish words with their pronunciation from Dansk Ordbog
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51 instances - 2 features - classes - 2 missing values
Nifty_750 (1)
Historic 3 mins data of nifty for past 2 years
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Carter
Marshall-Bell Ireland Joined 2020-12-27
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Brooke Jenkins
Reunion Joined 2020-12-26
0 uploads 0 activity 0 reach 0 impact
Marc
Help decade him attack activity important. Major medical enjoy data of hear become. Look office choose their treatment bring say. Challenge station take across. Respond second reality off.
Ferguson PLC Switzerland Joined 2020-12-25
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Ashley Hart
Yemen Joined 2020-12-24
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John
Remain authority store sometimes ever even respond. Interview shake only. Guess than value exactly support lawyer certain.
Simmons Inc Togo Joined 2020-12-23
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Kimberly Wilson
Free and owner instead write threat. Soldier serve chair network voice professor Mrs high.
Davis-Walter Joined 2020-12-23
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Clark
Develop with section particular. Sport heart turn six. Magazine campaign result result debate for order population. My executive test able.
Iraq Joined 2020-12-21
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Rachel
Have daughter firm process. Worry knowledge system best. Performance high property billion. Administration chance half black to boy perform.
Scott LLC Somalia Joined 2020-12-20
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keras.engine.sequential.Sequential.39edaf7b (1)
Automatically created keras flow.
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KDDCup09-Churn (2)
This is the full version of the KDD Cup 2009 dataset Customer Relationship Management (CRM) is a key element of modern marketing strategies. The KDD Cup 2009 offers the opportunity to work on large…
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50000 instances - 15001 features - 2 classes - 14616450 missing values