88 datasets found

The dataset used for the experiments in the paper, containing 28,147 compounds with a simple rule for classification.

Half Moon dataset

LEURN: a neural network architecture that learns univariate decision rules

The SQF dataset is a dataset used for classification tasks, and it contains sensitive attributes such as race.

Characterizes the complexity of classification problems using various measures.

The dataset used in the paper is a collection of 3 datasets: Iris, Wisconsin Breast Cancer, and Pima Indian Diabetes.

Standard data sets from UCI repository or Kaggle, including California Housing, Boston, Abalone, Auto, Red Wine, Concrete, Fish Toxicity, NBA salary, and others.

The MonuMAI dataset is a part-based object recognition dataset for classifying architectural styles of monument facades.

The dataset used in this paper is a collection of wine quality classification problems.

The dataset used in this paper is a collection of ionosphere classification problems.

The dataset used in the paper is a mushroom classification problem with 8124 instances.

The dataset consists of 24 raw statistical features used for training and validating the standard Random Forest classifier.

PROBEN1 is a set of neural network problems and benchmarking rules.

Hyperspectral images classification is a high technical remote sensing software. The purpose is to reproduce a thematic map. The HSI contains more than a hundred hyperspectral...

The dataset used in the paper is a collection of logistic classification problems described by Chang & Lin (2011) in the form of their library for support vector machines...

The MNIST data set is a dataset used for testing the performance of the DisDF.

The Ionosphere data set is a dataset used for testing the performance of the DisDF.

The Ecoli data set is a dataset used for testing the performance of the DisDF.

The Parkinsons data set is a dataset used for testing the performance of the DisDF.

The dataset used in the paper is MNIST-4.