Balance Scale

Donated on 4/21/1994

Balance scale weight & distance database

Dataset Characteristics

Multivariate

Subject Area

Social Science

Associated Tasks

Classification

Feature Type

Categorical

# Instances

625

# Features

4

Dataset Information

Additional Information

This data set was generated to model psychological experimental results. Each example is classified as having the balance scale tip to the right, tip to the left, or be balanced. The attributes are the left weight, the left distance, the right weight, and the right distance. The correct way to find the class is the greater of (left-distance * left-weight) and (right-distance * right-weight). If they are equal, it is balanced.

Has Missing Values?

No

Variables Table

Variable NameRoleTypeDescriptionUnitsMissing Values
right-distanceFeatureCategoricalL, B, Rno
right-weightFeatureCategorical1, 2, 3, 4, 5no
left-distanceFeatureCategorical1, 2, 3, 4, 5no
left-weightFeatureCategorical1, 2, 3, 4, 5no
classTargetCategorical1, 2, 3, 4, 5no

0 to 5 of 5

Additional Variable Information

1. Class Name: 3 (L, B, R) 2. Left-Weight: 5 (1, 2, 3, 4, 5) 3. Left-Distance: 5 (1, 2, 3, 4, 5) 4. Right-Weight: 5 (1, 2, 3, 4, 5) 5. Right-Distance: 5 (1, 2, 3, 4, 5)

Baseline Model Performance

Dataset Files

FileSize
balance-scale.data6.1 KB
balance-scale.names2.2 KB
Index132 Bytes

Papers Citing this Dataset

Robust Logistic Regression against Attribute and Label Outliers via Information Theoretic Learning

By Yuanhao Li, Badong Chen, Natsue Yoshimura, Yasuharu Koike. 2019

Published in ArXiv.

GrAMME: Semi-Supervised Learning using Multi-layered Graph Attention Models

By Uday Shanthamallu, Jayaraman Thiagarajan, Huan Song, Andreas Spanias. 2018

Published in

Noncrossing Ordinal Classification

By Xingye Qiao. 2015

Published in Statistics and Its Interface.

Semi-Supervised Nonlinear Distance Metric Learning via Forests of Max-Margin Cluster Hierarchies

By David Johnson, Caiming Xiong, Jason Corso. 2014

Published in ArXiv.

A New Incremental Learning Algorithm with Probabilistic Weights Using Extended Data Expression

By Kwangmo Yang, Anastasiya Kolesnikova, Won Lee. 2013

Published in J. Inform. and Commun. Convergence Engineering.

0 to 5 of 5

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Keywords

Creators

R. Siegler

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