gina_prior
OpenML dataset with id 1042
Author name not available (Why is that?)
Full work available at URL: https://api.openml.org/data/v1/download/53925/gina_prior.arff
Upload date: 6 October 2014
Dataset Characteristics
Number of classes: 2
Number of features: 785 (numeric: 784, symbolic: 1 and in total binary: 1 )
Number of instances: 3,468
Number of instances with missing values: 0
Number of missing values: 0
Author: Source: Unknown - Date unknown Please cite:
Note: derived from MNIST?
Datasets from the Agnostic Learning vs. Prior Knowledge Challenge (http://www.agnostic.inf.ethz.ch)
Dataset from: http://www.agnostic.inf.ethz.ch/datasets.php
Modified by TunedIT (converted to ARFF format)
GINA is digit recognition database
The task of GINA is handwritten digit recognition. For the "prior knowledge track" we chose the problem of separating one-digit odd numbers from one-digit even numbers. The original pixel map representation is provided. This is a two class classification problem with sparse continuous input variables, in which each class is composed of several clusters. It is a problem with heterogeneous classes.
Data type: non-sparse Number of features: 784 Number of examples and check-sum: Pos_ex Neg_ex Tot_ex Check_sum Train 1550 1603 3153 82735983.00 Valid 155 160 315 8243382.00
This dataset contains samples from both training and validation datasets.
This page was built for dataset: gina_prior
