34 datasets found

Student performance dataset is a regression task which contains 33 students as training and testing examples and their performance based on features such as average number of...

Boston house prices dataset is a classical linear regression task which contains 506 houses as training and testing examples and their prices based on features such as weighted...

PCQM4Mv2 dataset is used for graph regression tasks

The dataset used in this paper is the Brightdata dataset.

The dataset used in this paper is the Australian Credit dataset.

This paper describes a differentially private post-processing algorithm for learning attribute-aware fair regressors.

This paper describes a differentially private post-processing algorithm for learning attribute-aware fair regressors.

This paper describes a differentially private post-processing algorithm for learning attribute-aware fair regressors.

The dataset used in the paper is a motorcycle dataset, which is used to evaluate the proposed algorithm.

The Body Fat dataset is a regression problem in the simple machine learning dataset category. The instances are sought to predict body fat percentage based on body characteristics.

Inverse Sine Wave dataset

Tabular classification dataset

The dataset used in this paper is a regression problem, and it is a real-world regression task, that is, DB 4 comes from a real-world application, that is, computer activity...

The dataset used in this paper is a regression problem, and it is a real-world regression task, that is, DB 3 contains 1020 instances. Both the training and test sets are formed...

The dataset used in this paper is a regression problem, and it is a real-world regression task, that is, DB 2 contains 950 observations with nine input variables and one output...

The dataset used in this paper is a regression problem, and it is a function approximation example, that is, DB 1 was generated by a real-valued function [27]: f (x) =...

The Radon dataset is used to evaluate the performance of the proposed algorithm.

The dataset used in this paper is a sampled dataset for autoencoder-based regression models.

Python has gained widespread popularity in the fields of machine learning, artificial intelligence, and data engineering due to its effectiveness and extensive libraries. R, on...

The dataset used in the paper is not explicitly described, but it is mentioned that the authors used the two moons dataset for experiments.