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
some description
1 datasets, 1 tasks, 1 flows, 1 runs
some description
1 datasets, 1 tasks, 1 flows, 1 runs
some description
1 datasets, 1 tasks, 1 flows, 1 runs
some description
1 datasets, 1 tasks, 1 flows, 1 runs
some description
1 datasets, 1 tasks, 1 flows, 1 runs
some description
1 datasets, 1 tasks, 1 flows, 1 runs
regression related omics tasks
8 datasets, 8 tasks, 0 flows, 0 runs
regression related omics tasks
8 datasets, 8 tasks, 0 flows, 0 runs
Multiclass classification datasets
4 datasets, 4 tasks, 0 flows, 0 runs
Multiclass classification datasets
4 datasets, 4 tasks, 0 flows, 0 runs
Multiclass classification datasets
4 datasets, 4 tasks, 0 flows, 0 runs
This collection complements the Padding Attacks benchmark datasets serves as a valuable benchmark training set for multi-class classification tasks or detecting information leakage via error code or…
96 datasets, 96 tasks, 0 flows, 0 runs
a gpt ai model for carrtesi
1 datasets, 1 tasks, 0 flows, 0 runs
a gpt ai model for carrtesi
1 datasets, 1 tasks, 0 flows, 0 runs
A set of tasks related to the prediction of online gambling self-exclusion originally appearing in https://doi.org/10.1080/14459795.2013.841721 and https://doi.org/10.1080/14459795.2016.1151913
2 datasets, 2 tasks, 0 flows, 0 runs
Testing FBR
1 datasets, 1 tasks, 0 flows, 0 runs
Testing FBR
1 datasets, 1 tasks, 0 flows, 0 runs
Testing FBR
1 datasets, 1 tasks, 0 flows, 0 runs
Testing FBR
1 datasets, 1 tasks, 0 flows, 0 runs
Testing FBR
1 datasets, 1 tasks, 0 flows, 0 runs
nlp
1 datasets, 1 tasks, 0 flows, 0 runs
nlp
1 datasets, 1 tasks, 0 flows, 0 runs
nlp
1 datasets, 1 tasks, 0 flows, 0 runs
nlp
1 datasets, 1 tasks, 0 flows, 0 runs
nlp
1 datasets, 1 tasks, 0 flows, 0 runs
nlp
1 datasets, 1 tasks, 0 flows, 0 runs
nlp
1 datasets, 1 tasks, 0 flows, 0 runs
Classification/Risk prediction for Tabular data related to MI(Coronary heart disease)
1 datasets, 1 tasks, 0 flows, 0 runs
Classification/Risk prediction for Tabular data related to MI(Coronary heart disease)
1 datasets, 1 tasks, 0 flows, 0 runs
illustrating how to create a benchmark suite
2 datasets, 2 tasks, 0 flows, 0 runs
illustrating how to create a benchmark suite
2 datasets, 2 tasks, 0 flows, 0 runs
illustrating how to create a benchmark suite
2 datasets, 2 tasks, 0 flows, 0 runs
illustrating how to create a benchmark suite
250 datasets, 250 tasks, 0 flows, 0 runs
test
1 datasets, 1 tasks, 0 flows, 0 runs
1)BUY #BANKNIFTY 45300 PE ABOVE -490 TARGET- 40 /70/100/200/250 Point SL-450 2)BUY #BANKNIFTY 45300 PE ABOVE -550 TARGET- 40 /70/100/200/250 Point SL-500 3)BUY#ALKEM 4100 CE ABOVE -218 TARGE- 228,250…
1 datasets, 1 tasks, 0 flows, 0 runs
1)BUY #BANKNIFTY 45300 PE ABOVE -490 TARGET- 40 /70/100/200/250 Point SL-450 2)BUY #BANKNIFTY 45300 PE ABOVE -550 TARGET- 40 /70/100/200/250 Point SL-500 3)BUY#ALKEM 4100 CE ABOVE -218 TARGE- 228,250…
1 datasets, 1 tasks, 0 flows, 0 runs
This collection complements the Timing Attacks benchmark datasets and serves as a valuable training set for multi-class classification tasks or detecting information leakage in OpenSSL. For detailed…
87 datasets, 87 tasks, 0 flows, 0 runs
packet_priority_classification
1 datasets, 1 tasks, 0 flows, 0 runs
packet_priority_classification
1 datasets, 1 tasks, 0 flows, 0 runs
Hard tabular datasets from the TabZilla study.
36 datasets, 36 tasks, 0 flows, 0 runs
Teste
1 datasets, 1 tasks, 0 flows, 0 runs
Teste
1 datasets, 1 tasks, 0 flows, 0 runs
digital_text
1 datasets, 1 tasks, 0 flows, 0 runs
digital_text
1 datasets, 1 tasks, 0 flows, 0 runs
digital_text
1 datasets, 1 tasks, 0 flows, 0 runs
digital_text
1 datasets, 1 tasks, 0 flows, 0 runs
Inclusion Criteria: * There are between 500 and 100000 observations. * There are less than 5000 features after one-hot encoding all categorical features. * The dataset is not in a sparse format. * The…
35 datasets, 35 tasks, 0 flows, 0 runs
We investigate the performance of a wide range of regression algorithms on a wide range of datasets to better understand when they perform well and when they don't. This will yield a meta-dataset that…
3 datasets, 3 tasks, 0 flows, 0 runs
TuningTreesClassification
2 datasets, 2 tasks, 0 flows, 0 runs
TuningTreesClassification
2 datasets, 2 tasks, 0 flows, 0 runs
TuningTreesClassification
2 datasets, 2 tasks, 0 flows, 0 runs
TuningTreesClassification
2 datasets, 2 tasks, 0 flows, 0 runs
We introduce how we configured benchmark datasets to properly evaluate the performance of our proposed method, STCC: Semi-Supervised Learning for Tabular Datasets with Continuous and Categorical…
24 datasets, 24 tasks, 0 flows, 0 runs
this is for test
24 datasets, 24 tasks, 0 flows, 0 runs
Hi there
1 datasets, 1 tasks, 0 flows, 0 runs
Hi there
1 datasets, 1 tasks, 0 flows, 0 runs
Suite containing the datasets used in the "classification on numerical features" benchmark of the tabular data benchmarks https://github.com/LeoGrin/tabular-benchmark The datasets have been…
16 datasets, 16 tasks, 0 flows, 0 runs
Suite containing the datasets used in the "regression on numerical features" benchmark of the tabular data benchmarks https://github.com/LeoGrin/tabular-benchmark The datasets have been transformed as…
19 datasets, 19 tasks, 0 flows, 0 runs
Suite containing the datasets used in the "regression on both numerical and categorical features" benchmark of the tabular data benchmarks https://github.com/LeoGrin/tabular-benchmark The datasets…
17 datasets, 17 tasks, 0 flows, 0 runs
Suite containing the datasets used in the "classification on both numerical and categorical features" benchmark of the tabular data benchmarks https://github.com/LeoGrin/tabular-benchmark The datasets…
7 datasets, 7 tasks, 0 flows, 0 runs
Meta Album is a meta-dataset created for few-shot learning, meta-learning, continual learning, AutoML, and more. The Extended version contains the full datasets. Learn more about Meta-Album at…
27 datasets, 27 tasks, 0 flows, 0 runs
Meta Album is a meta-dataset created for few-shot learning, meta-learning, continual learning, AutoML, and more. The Mini version contains 40 randomly selected examples for each class (hence the…
30 datasets, 30 tasks, 0 flows, 0 runs
Meta Album is a meta-dataset created for few-shot learning, meta-learning, continual learning, AutoML, and more. The Micro version is meant for quick experimentation. It only contains 20 randomly…
30 datasets, 30 tasks, 0 flows, 0 runs
bot
1 datasets, 1 tasks, 0 flows, 0 runs
bot
1 datasets, 1 tasks, 0 flows, 0 runs
bot
1 datasets, 1 tasks, 0 flows, 0 runs
bot
1 datasets, 1 tasks, 0 flows, 0 runs
a study with no runs attached
0 datasets, 0 tasks, 0 flows, 0 runs
Pange
1 datasets, 1 tasks, 1 flows, 1 runs
Pange
1 datasets, 1 tasks, 1 flows, 1 runs
Suite containing the datasets used in the "classification on numerical and categorical features" benchmark of the tabular data benchmarks https://github.com/LeoGrin/tabular-benchmark The datasets has…
7 datasets, 7 tasks, 0 flows, 0 runs
Suite containing the datasets used in the "classification on numerical and categorical features" benchmark of the tabular data benchmarks https://github.com/LeoGrin/tabular-benchmark The datasets has…
7 datasets, 7 tasks, 0 flows, 0 runs
Suite containing the datasets used in the "regression on numerical and categorical features" benchmark of the tabular data benchmarks https://github.com/LeoGrin/tabular-benchmark The datasets has been…
13 datasets, 13 tasks, 0 flows, 0 runs
Suite containing the datasets used in the "classification on numerical features" benchmark of the tabular data benchmarks https://github.com/LeoGrin/tabular-benchmark The datasets has been transformed…
15 datasets, 15 tasks, 0 flows, 0 runs
Suite containing the datasets used in the "regression on numerical features" benchmark of the tabular data benchmarks https://github.com/LeoGrin/tabular-benchmark The datasets has been transformed as…
20 datasets, 20 tasks, 0 flows, 0 runs
An study reporting results of a decision tree with different splitter.
2 datasets, 2 tasks, 1 flows, 2 runs
An example study reporting results of a decision stump.
2 datasets, 2 tasks, 1 flows, 2 runs
An example study reporting results of a decision stump.
1 datasets, 1 tasks, 1 flows, 1 runs
A complimentary set of tasks to the AutoML benchmark that can be used as a training set for meta-learning as suggested by Feurer et al. in the paper "Auto-Sklearn 2.0: Hands-free AutoML via…
208 datasets, 208 tasks, 0 flows, 0 runs
After exploring dierent subsets, the subset consisting of 50% of the total datasets.
29 datasets, 29 tasks, 0 flows, 0 runs
illustrating how to create a benchmark suite
250 datasets, 250 tasks, 0 flows, 0 runs
illustrating how to create a benchmark suite
250 datasets, 250 tasks, 0 flows, 0 runs
Test suite for the Python tutorial on benchmark suites
20 datasets, 20 tasks, 0 flows, 0 runs
Test suite for the Python tutorial on benchmark suites
20 datasets, 20 tasks, 0 flows, 0 runs
Test suite for the Python tutorial on benchmark suites
20 datasets, 20 tasks, 0 flows, 0 runs
Description
2 datasets, 2 tasks, 1 flows, 2 runs
Description
39 datasets, 39 tasks, 1 flows, 39 runs
illustrating how to create a benchmark suite
251 datasets, 251 tasks, 0 flows, 0 runs
case_Classifier for the PHM
1 datasets, 1 tasks, 2 flows, 2 runs
case_Regression for the PHM
1 datasets, 1 tasks, 3 flows, 3 runs
Collection of all classification tasks for the AutoML Benchmark (https://github.com/openml/automlbenchmark).
71 datasets, 71 tasks, 0 flows, 0 runs
Collection of new classification tasks for the AutoML Benchmark (https://github.com/openml/automlbenchmark).
29 datasets, 29 tasks, 0 flows, 0 runs
Collection of regression tasks for the AutoML Benchmark (https://github.com/openml/automlbenchmark).
33 datasets, 33 tasks, 0 flows, 0 runs
15% More difficult and discriminative Percentage of instances with high Discrimination parameter values Dataset :: Percentage of instances vowel :: 92% breast-w :: 92% monks-problems-1 :: 89%…
8 datasets, 8 tasks, 0 flows, 0 runs
10% More difficult and discriminative of the TesteCC18 study Porcentagem de instancias com valores altos do parametro Discriminacao Dataset :: Percentual de instancias banknote-authentication :: 100%…
12 datasets, 12 tasks, 0 flows, 0 runs
Testing how to create a benchmark suite
60 datasets, 60 tasks, 0 flows, 0 runs
Benchmark suite for fair machine learning.
0 datasets, 0 tasks, 0 flows, 0 runs
A benchmark suite to investigate how Deep Learning scales with dataset size. Building upon the prior work from https://openml.github.io/automlbenchmark/
62 datasets, 62 tasks, 0 flows, 0 runs
IRT for regression tasks/datasets
0 datasets, 0 tasks, 0 flows, 0 runs