This is a collection of datasets that can be used to evaluate Confidence Interval methods for the Generalization Error. The task splits can be ignored. For more information, see…
18 datasets, 18 tasks, 0 flows, 0 runs
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uploader_id : 30127 - estimation_procedure : 10-fold Crossvalidation - target_feature : Target
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uploader_id : 30703 - estimation_procedure : 10-fold Crossvalidation - target_feature : class
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uploader_id : 30703 - estimation_procedure : 10-fold Crossvalidation - target_feature : SLUMP_cm,FLOW_cm,Compressive_Strength_Mpa
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uploader_id : 30703 - estimation_procedure : 10-fold Crossvalidation - target_feature : reference
From original source: ----- The dataset consists of 384 features extracted from CT images. The class variable is numeric and denotes the relative location of the CT slice on the axial axis of the…
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53500 instances - 385 features - 0 classes - 0 missing values
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uploader_id : 30703 - estimation_procedure : 10-fold Crossvalidation
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uploader_id : 30703 - estimation_procedure : 10-fold Crossvalidation - target_feature : Compressive_Strength_Mpa
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uploader_id : 30703 - estimation_procedure : 10-fold Crossvalidation - target_feature : FLOW_cm
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uploader_id : 30703 - estimation_procedure : 10-fold Crossvalidation - target_feature : SLUMP_cm
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uploader_id : 30703 - estimation_procedure : 10-fold Crossvalidation - target_feature : S
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uploader_id : 30703 - estimation_procedure : 10-fold Crossvalidation - target_feature : stab
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uploader_id : 30703 - estimation_procedure : 10-fold Crossvalidation - target_feature : stabf
From original source: ----- The local stability analysis of the 4-node star system (electricity producer is in the center) implementing Decentral Smart Grid Control concept. Additional Information The…
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10000 instances - 13 features - 0 classes - 0 missing values
From original source: ----- The local stability analysis of the 4-node star system (electricity producer is in the center) implementing Decentral Smart Grid Control concept. Additional Information The…
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10000 instances - 13 features - 2 classes - 0 missing values
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uploader_id : 30703 - estimation_procedure : 10-fold Crossvalidation
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uploader_id : 30703 - estimation_procedure : 10-fold Crossvalidation - target_feature : class
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uploader_id : 30703 - estimation_procedure : 10-fold Crossvalidation - target_feature : Revenue
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uploader_id : 30703 - estimation_procedure : 10-fold Crossvalidation - target_feature : class
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uploader_id : 30703 - estimation_procedure : 10-fold Crossvalidation - target_feature : Team_won
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uploader_id : 30703 - estimation_procedure : 10-fold Crossvalidation - target_feature : Classification
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uploader_id : 30703 - estimation_procedure : 10-fold Crossvalidation - target_feature : 13
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uploader_id : 30703 - estimation_procedure : 10-fold Crossvalidation - target_feature : 8
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uploader_id : 30703 - estimation_procedure : 10-fold Crossvalidation - target_feature : LONGITUDE
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uploader_id : 30703 - estimation_procedure : 10-fold Crossvalidation - target_feature : LATITUDE
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uploader_id : 30703 - estimation_procedure : 10-fold Crossvalidation - target_feature : 4
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uploader_id : 30703 - estimation_procedure : 10-fold Crossvalidation - target_feature : pm2.5
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uploader_id : 30703 - estimation_procedure : 10-fold Crossvalidation - target_feature : charges
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uploader_id : 30703 - estimation_procedure : 10-fold Crossvalidation - target_feature : 23
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uploader_id : 30703 - estimation_procedure : 10-fold Crossvalidation - target_feature : price
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uploader_id : 30703 - estimation_procedure : 10-fold Crossvalidation - target_feature : 9
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uploader_id : 30703 - estimation_procedure : 10-fold Crossvalidation - target_feature : Appliances
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uploader_id : 30703 - estimation_procedure : 10-fold Crossvalidation - target_feature : 127
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uploader_id : 30703 - estimation_procedure : 10-fold Crossvalidation - target_feature : target
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uploader_id : 30703 - estimation_procedure : 10-fold Crossvalidation - target_feature : Classes
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uploader_id : 30703 - estimation_procedure : 10-fold Crossvalidation - target_feature : Churn
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uploader_id : 30703 - estimation_procedure : 10-fold Crossvalidation - target_feature : target
From original source: ----- The dataset contains count of public bicycles rented per hour in the Seoul Bike Sharing System, with corresponding weather data and holiday information Additional…
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8760 instances - 14 features - 0 classes - 0 missing values
From original source: ----- Data set containing values for 8 attributes (molecular descriptors) of 546 chemicals used to predict quantitative acute aquatic toxicity towards Daphnia Magna.. Additional…
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546 instances - 9 features - 0 classes - 0 missing values
From original source: ----- The UJIIndoorLoc is a Multi-Building Multi-Floor indoor localization database to test Indoor Positioning System that rely on WLAN/WiFi fingerprint. Additional Information…
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21048 instances - 526 features - 0 classes - 0 missing values
From original source: ----- The UJIIndoorLoc is a Multi-Building Multi-Floor indoor localization database to test Indoor Positioning System that rely on WLAN/WiFi fingerprint. Additional Information…
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21048 instances - 526 features - 0 classes - 0 missing values
From original source: ----- Data was from a simulation of a servo system Additional Information Ross Quinlan: This data was given to me by Karl Ulrich at MIT in 1986. I didn't record his description…
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167 instances - 5 features - 0 classes - 0 missing values
From original source: ----- Context Machine Learning with R by Brett Lantz is a book that provides an introduction to machine learning using R. As far as I can tell, Packt Publishing does not make its…
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1338 instances - 7 features - 0 classes - 0 missing values
From original source: ----- KEGG Metabolic pathways modeled as directed relation network. Variety of graphical features presented. Additional Information KEGG Metabolic pathways can be realized into…
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53413 instances - 23 features - 0 classes - 0 missing values
From original source: ----- Communities within the United States. The data combines socio-economic data from the 1990 US Census, law enforcement data from the 1990 US LEMAS survey, and crime data from…
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209 instances - 9 features - 0 classes - 0 missing values
From original source: ----- Communities within the United States. The data combines socio-economic data from the 1990 US Census, law enforcement data from the 1990 US LEMAS survey, and crime data from…
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1994 instances - 123 features - 0 classes - 36851 missing values
From original source: ----- This hourly data set contains the PM2.5 data of US Embassy in Beijing. Meanwhile, meteorological data from Beijing Capital International Airport are also included.…
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41757 instances - 12 features - 0 classes - 0 missing values
From original source: ----- About this file What are the things that a potential home buyer considers before purchasing a house? The location, the size of the property, vicinity to offices, schools,…
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13320 instances - 8 features - 0 classes - 682 missing values
From original source: ----- Additional Information The data set is at 10 min for about 4.5 months. The house temperature and humidity conditions were monitored with a ZigBee wireless sensor network.…
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19735 instances - 28 features - 0 classes - 0 missing values
From original source: ----- As part of our continued commitment towards the WWW community and its success, we are again making available the entire data sets for this set of surveys. This enables…
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10108 instances - 69 features - 2 classes - 309 missing values
From original source: ----- Additional Information Information about customers consists of 86 variables and includes product usage data and socio-demographic data derived from zip area codes. The data…
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9822 instances - 86 features - 2 classes - 0 missing values
From original source: ----- Context "Predict behavior to retain customers. You can analyze all relevant customer data and develop focused customer retention programs." [IBM Sample Data Sets] Content…
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7043 instances - 20 features - 2 classes - 11 missing values
From original source: ----- Additional Information The dataset includes 244 instances that regroup a data of two regions of Algeria,namely the Bejaia region located in the northeast of Algeria and the…
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243 instances - 14 features - 2 classes - 0 missing values
tester
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536 instances - 1 features - classes - 0 missing values
Fuel Datasets in India States
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41406 instances - 6 features - classes - 24 missing values
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8218, f_measure: 0.7515, kappa: 0.4469, kb_relative_information_score: 0.3057, mean_absolute_error: 0.3204, mean_prior_absolute_error: 0.4545, weighted_recall: 0.7552, number_of_instances: 768, precision: 0.7503, predictive_accuracy: 0.7552, prior_entropy: 0.9331, relative_absolute_error: 0.7051, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4019, root_relative_squared_error: 0.8433, unweighted_recall: 0.7176,
Algorithm performane prediction problem on 1120 5d MA-BBOB test problems using ELA features to learn which of five algorithms has the highest AUCC.
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1120 instances - 46 features - 0 classes - 0 missing values
Algorithm performane prediction problem on 1120 5d MA-BBOB test problems using ELA features to learn which of five algorithms has the highest AUCC.
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1120 instances - 46 features - 0 classes - 0 missing values
Algorithm performane prediction problem on 1120 5d MA-BBOB test problems using ELA features to learn which of five algorithms has the highest AUCC.
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1120 instances - 46 features - 0 classes - 0 missing values
Algorithm performane prediction problem on 1120 5d MA-BBOB test problems using ELA features to learn which of five algorithms has the highest AUCC.
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1120 instances - 46 features - 0 classes - 0 missing values
Algorithm performane prediction problem on 1120 5d MA-BBOB test problems using ELA features to learn which of five algorithms has the highest AUCC.
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1120 instances - 46 features - 0 classes - 0 missing values
Algorithm selection problem on 1120 5d MA-BBOB test problems using ELA features to learn which of five algorithms has the highest AUCC.
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1120 instances - 46 features - 4 classes - 0 missing values
Algorithm performane prediction problem on 1120 2d MA-BBOB test problems using ELA features to learn which of five algorithms has the highest AUCC.
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1120 instances - 46 features - 0 classes - 0 missing values
Algorithm performane prediction problem on 1120 2d MA-BBOB test problems using ELA features to learn which of five algorithms has the highest AUCC.
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1120 instances - 46 features - 0 classes - 0 missing values
Algorithm performane prediction problem on 1120 2d MA-BBOB test problems using ELA features to learn which of five algorithms has the highest AUCC.
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1120 instances - 46 features - 0 classes - 0 missing values
Algorithm performane prediction problem on 1120 2d MA-BBOB test problems using ELA features to learn which of five algorithms has the highest AUCC.
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1120 instances - 46 features - 0 classes - 0 missing values
Algorithm performane prediction problem on 1120 2d MA-BBOB test problems using ELA features to learn which of five algorithms has the highest AUCC.
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1120 instances - 46 features - 0 classes - 0 missing values
Algorithm selection problem on 1120 2d MA-BBOB test problems using ELA features to learn which of five algorithms has the highest AUCC.
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1120 instances - 46 features - 5 classes - 0 missing values
The dataset includes several weather parameter and and information about campsite utilisation in germany. The data is available on a montly basis and separated by the german bundeslander. The data…
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4255 instances - 36 features - classes - 3334 missing values
daily pickup data for 329 FHV companies from January 2015 through August 2015. From original source: ----- There is also a file other-FHV-data-jan-aug-2015.csv containing daily pickup data for 329 FHV…
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29826 instances - 5 features - classes - 9276 missing values
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8245, f_measure: 0.7636, kappa: 0.4726, kb_relative_information_score: 0.3104, mean_absolute_error: 0.318, mean_prior_absolute_error: 0.4545, weighted_recall: 0.7682, number_of_instances: 768, precision: 0.7631, predictive_accuracy: 0.7682, prior_entropy: 0.9331, relative_absolute_error: 0.6997, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4006, root_relative_squared_error: 0.8405, unweighted_recall: 0.7285,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8267, f_measure: 0.771, kappa: 0.4885, kb_relative_information_score: 0.3145, mean_absolute_error: 0.3165, mean_prior_absolute_error: 0.4545, weighted_recall: 0.776, number_of_instances: 768, precision: 0.7711, predictive_accuracy: 0.776, prior_entropy: 0.9331, relative_absolute_error: 0.6965, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3991, root_relative_squared_error: 0.8373, unweighted_recall: 0.7354,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8242, f_measure: 0.7686, kappa: 0.4847, kb_relative_information_score: 0.3092, mean_absolute_error: 0.3191, mean_prior_absolute_error: 0.4545, weighted_recall: 0.7721, number_of_instances: 768, precision: 0.7677, predictive_accuracy: 0.7721, prior_entropy: 0.9331, relative_absolute_error: 0.7022, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4007, root_relative_squared_error: 0.8407, unweighted_recall: 0.7358,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8315, f_measure: 0.761, kappa: 0.4666, kb_relative_information_score: 0.3146, mean_absolute_error: 0.3166, mean_prior_absolute_error: 0.4545, weighted_recall: 0.7656, number_of_instances: 768, precision: 0.7604, predictive_accuracy: 0.7656, prior_entropy: 0.9331, relative_absolute_error: 0.6966, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.397, root_relative_squared_error: 0.8329, unweighted_recall: 0.7256,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8281, f_measure: 0.7633, kappa: 0.4716, kb_relative_information_score: 0.314, mean_absolute_error: 0.317, mean_prior_absolute_error: 0.4545, weighted_recall: 0.7682, number_of_instances: 768, precision: 0.763, predictive_accuracy: 0.7682, prior_entropy: 0.9331, relative_absolute_error: 0.6975, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.398, root_relative_squared_error: 0.8351, unweighted_recall: 0.7276,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.83, f_measure: 0.7595, kappa: 0.4632, kb_relative_information_score: 0.3157, mean_absolute_error: 0.3167, mean_prior_absolute_error: 0.4545, weighted_recall: 0.7643, number_of_instances: 768, precision: 0.7589, predictive_accuracy: 0.7643, prior_entropy: 0.9331, relative_absolute_error: 0.6967, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3973, root_relative_squared_error: 0.8335, unweighted_recall: 0.7238,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8248, f_measure: 0.771, kappa: 0.4885, kb_relative_information_score: 0.3106, mean_absolute_error: 0.3193, mean_prior_absolute_error: 0.4545, weighted_recall: 0.776, number_of_instances: 768, precision: 0.7711, predictive_accuracy: 0.776, prior_entropy: 0.9331, relative_absolute_error: 0.7025, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4003, root_relative_squared_error: 0.8398, unweighted_recall: 0.7354,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8254, f_measure: 0.7683, kappa: 0.4838, kb_relative_information_score: 0.3124, mean_absolute_error: 0.3183, mean_prior_absolute_error: 0.4545, weighted_recall: 0.7721, number_of_instances: 768, precision: 0.7675, predictive_accuracy: 0.7721, prior_entropy: 0.9331, relative_absolute_error: 0.7003, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3996, root_relative_squared_error: 0.8383, unweighted_recall: 0.735,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8279, f_measure: 0.7674, kappa: 0.4822, kb_relative_information_score: 0.315, mean_absolute_error: 0.317, mean_prior_absolute_error: 0.4545, weighted_recall: 0.7708, number_of_instances: 768, precision: 0.7664, predictive_accuracy: 0.7708, prior_entropy: 0.9331, relative_absolute_error: 0.6974, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3984, root_relative_squared_error: 0.8358, unweighted_recall: 0.7348,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8264, f_measure: 0.7521, kappa: 0.4459, kb_relative_information_score: 0.3129, mean_absolute_error: 0.3177, mean_prior_absolute_error: 0.4545, weighted_recall: 0.7578, number_of_instances: 768, precision: 0.7518, predictive_accuracy: 0.7578, prior_entropy: 0.9331, relative_absolute_error: 0.699, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3996, root_relative_squared_error: 0.8384, unweighted_recall: 0.7144,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8247, f_measure: 0.7553, kappa: 0.4552, kb_relative_information_score: 0.3066, mean_absolute_error: 0.3205, mean_prior_absolute_error: 0.4545, weighted_recall: 0.7591, number_of_instances: 768, precision: 0.7542, predictive_accuracy: 0.7591, prior_entropy: 0.9331, relative_absolute_error: 0.7051, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4008, root_relative_squared_error: 0.841, unweighted_recall: 0.7215,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8252, f_measure: 0.7654, kappa: 0.4757, kb_relative_information_score: 0.3071, mean_absolute_error: 0.3196, mean_prior_absolute_error: 0.4545, weighted_recall: 0.7708, number_of_instances: 768, precision: 0.7655, predictive_accuracy: 0.7708, prior_entropy: 0.9331, relative_absolute_error: 0.7033, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4006, root_relative_squared_error: 0.8404, unweighted_recall: 0.7288,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8292, f_measure: 0.7597, kappa: 0.4655, kb_relative_information_score: 0.3114, mean_absolute_error: 0.3178, mean_prior_absolute_error: 0.4545, weighted_recall: 0.763, number_of_instances: 768, precision: 0.7586, predictive_accuracy: 0.763, prior_entropy: 0.9331, relative_absolute_error: 0.6993, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.399, root_relative_squared_error: 0.837, unweighted_recall: 0.7271,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8211, f_measure: 0.7707, kappa: 0.4887, kb_relative_information_score: 0.304, mean_absolute_error: 0.3211, mean_prior_absolute_error: 0.4545, weighted_recall: 0.7747, number_of_instances: 768, precision: 0.7701, predictive_accuracy: 0.7747, prior_entropy: 0.9331, relative_absolute_error: 0.7064, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4025, root_relative_squared_error: 0.8444, unweighted_recall: 0.737,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8252, f_measure: 0.763, kappa: 0.472, kb_relative_information_score: 0.3102, mean_absolute_error: 0.3181, mean_prior_absolute_error: 0.4545, weighted_recall: 0.7669, number_of_instances: 768, precision: 0.7621, predictive_accuracy: 0.7669, prior_entropy: 0.9331, relative_absolute_error: 0.6999, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4003, root_relative_squared_error: 0.8399, unweighted_recall: 0.7292,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8268, f_measure: 0.7651, kappa: 0.476, kb_relative_information_score: 0.3126, mean_absolute_error: 0.3177, mean_prior_absolute_error: 0.4545, weighted_recall: 0.7695, number_of_instances: 768, precision: 0.7645, predictive_accuracy: 0.7695, prior_entropy: 0.9331, relative_absolute_error: 0.699, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3988, root_relative_squared_error: 0.8367, unweighted_recall: 0.7304,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8227, f_measure: 0.7684, kappa: 0.4826, kb_relative_information_score: 0.31, mean_absolute_error: 0.3192, mean_prior_absolute_error: 0.4545, weighted_recall: 0.7734, number_of_instances: 768, precision: 0.7684, predictive_accuracy: 0.7734, prior_entropy: 0.9331, relative_absolute_error: 0.7024, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4003, root_relative_squared_error: 0.8399, unweighted_recall: 0.7325,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8282, f_measure: 0.7728, kappa: 0.4928, kb_relative_information_score: 0.3112, mean_absolute_error: 0.3185, mean_prior_absolute_error: 0.4545, weighted_recall: 0.7773, number_of_instances: 768, precision: 0.7726, predictive_accuracy: 0.7773, prior_entropy: 0.9331, relative_absolute_error: 0.7007, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3981, root_relative_squared_error: 0.8353, unweighted_recall: 0.7381,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8288, f_measure: 0.758, kappa: 0.4597, kb_relative_information_score: 0.315, mean_absolute_error: 0.3168, mean_prior_absolute_error: 0.4545, weighted_recall: 0.763, number_of_instances: 768, precision: 0.7575, predictive_accuracy: 0.763, prior_entropy: 0.9331, relative_absolute_error: 0.697, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3985, root_relative_squared_error: 0.836, unweighted_recall: 0.7219,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8287, f_measure: 0.7616, kappa: 0.4672, kb_relative_information_score: 0.31, mean_absolute_error: 0.3191, mean_prior_absolute_error: 0.4545, weighted_recall: 0.7669, number_of_instances: 768, precision: 0.7615, predictive_accuracy: 0.7669, prior_entropy: 0.9331, relative_absolute_error: 0.7022, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3987, root_relative_squared_error: 0.8365, unweighted_recall: 0.7249,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.828, f_measure: 0.7562, kappa: 0.4567, kb_relative_information_score: 0.3139, mean_absolute_error: 0.3168, mean_prior_absolute_error: 0.4545, weighted_recall: 0.7604, number_of_instances: 768, precision: 0.7553, predictive_accuracy: 0.7604, prior_entropy: 0.9331, relative_absolute_error: 0.6971, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3987, root_relative_squared_error: 0.8364, unweighted_recall: 0.7216,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8262, f_measure: 0.7689, kappa: 0.4844, kb_relative_information_score: 0.3136, mean_absolute_error: 0.317, mean_prior_absolute_error: 0.4545, weighted_recall: 0.7734, number_of_instances: 768, precision: 0.7686, predictive_accuracy: 0.7734, prior_entropy: 0.9331, relative_absolute_error: 0.6976, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3995, root_relative_squared_error: 0.8383, unweighted_recall: 0.7342,
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…
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Description: The "wheel_of_fortune.csv" dataset is a structured collection crafted to support analyses and applications related to the popular game show "Wheel of Fortune." This dataset incorporates…
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Quarterly Database for Macroeconomic Research From original website: ----- FRED-MD and FRED-QD are large macroeconomic databases designed for the empirical analysis of 'big data'. The datasets of…
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258 instances - 204 features - classes - 0 missing values
Electricity Load Diagrams between 2011 and 2014, resampled hourly. From original source: ----- Data set has no missing values. Values are in kW of each 15 min. To convert values in kWh values must be…
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26305 instances - 319 features - classes - 0 missing values
data
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207 instances - 61 features - classes - 0 missing values
Description: The 'wheel_of_fortune.csv' dataset is an intriguing collection designed for various applications, including natural language processing, game development, and cultural studies. It…
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Description: The dataset named 'wheel_of_fortune.csv' is carefully curated for enthusiasts and researchers interested in linguistic patterns, game design, and computational linguistics analysis. It…
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Description: The Student_performance_data_.csv dataset is a comprehensive collection of data aimed at analyzing the factors influencing student performance across various dimensions. This dataset…
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2392 instances - 15 features - classes - 0 missing values