This section describes main characteristics of the balance data set and its attributes:
General information
Balance Scale data set |
Type | Classification | Origin | Real world |
Features | 4 | (Real / Integer / Nominal) | (4 / 0 / 0) |
Instances | 625 |
Classes | 3 |
Missing values? | No |
Attribute description
Attribute | Domain |
Left-weight | [1.0, 5.0] |
Left-distance | [1.0, 5.0] |
Right-weight | [1.0, 5.0] |
Right-distance | [1.0, 5.0] |
Balance_scale | {L,B,R} |
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.
In this section you can download some files related to the balance data set:
- The complete data set already formatted in KEEL format can be downloaded from
here.
- A copy of the data set already partitioned by means of a 10-folds cross validation procedure can be downloaded from here.
- A copy of the data set already partitioned by means of a 5-folds cross validation procedure can be downloaded from here.
- The header file associated to this data set can be downloaded from here.
- This is not a native data set from the KEEL project. It has been obtained from the UCI Machine Learning Repository . The original page where the data set can be found is: http://archive.ics.uci.edu/ml/datasets/Balance+Scale.
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