91 datasets found

Time-series datasets for classification tasks

Time-series datasets for classification tasks

The dataset used in the paper is a Big Data classification problem.

The dataset used in this paper for abnormal red blood cell classification.

The National Agriculture Imagery Program (NAIP) dataset contains aerial photographs of agricultural lands.

The ModelNet-10 dataset is a benchmark for 3D point cloud classification and semantic segmentation. It contains 4,899 untextured CAD models divided into 10 categories.

The EIS data set, Z, associated with this article was created by QS. It comprises approximately 9,300 synthetic impedance spectra, z ∈ Z that are vectors of impedances, z ∈ Cn.

The proposed processing pipeline encom- passes two fundamental parts: regions of interest mask generation, followed by the application of hyperspectral data processing...

The paper discusses the use of multi-objective Bayesian optimization for hyperparameter transfer in topic models.

The Iris dataset is a multivariate dataset introduced by Sir Ronald Fisher in his 1936 paper "The use of multiple measurements in taxonomic problems". It contains 150 samples...

The dataset used for training the CNN in cough detection is composed of various modified audio clips gathered from open-source online sources. Each of these audio files...

The dataset used in this study consists of three clinical datasets: oncology, hepatitis, and diabetes.

The dataset used in the paper is a classification dataset, specifically poker.

The dataset used in the paper is a classification dataset, specifically tic-tac-toe, breast-cancer, poker, and mnist.

The Bonobo dataset, the classification models and the training methods presented are available on the Project GitHub page

The Bonobo dataset, the classification models and the training methods presented are available on the Project GitHub page

Zero-shot learning (ZSL) aims to classify objects that are not observed or seen during training. It relies on class semantic description to transfer knowledge from the seen...

Caltech-UCSD Birds (CUB) 200-2011 is a frequently used benchmark for unsupervised image segmentation. It consists of 11,788 images from 200 bird species.

The Abalone dataset has 4177 observation 8 covariates. Sex is a nominal variable with 3 categories: Male, Female and Infant. Length (mm) is the longest shell measurement,...

A commonly observed pattern in machine learning models is an underprediction of the target feature, with the model’s predicted target rate for members of a given category...