KEEL: A software tool to assess evolutionary algorithms for Data Mining problems (regression, classification, clustering, pattern mining and so on)

KEEL-dataset - data set description

Teaching Assistant Evaluation data set

Description
Files and additional references

Description

This section describes main characteristics of the tae data set and its attributes:

General information

Teaching Assistant Evaluation data set
Type	Classification	Origin	Real world
Features	5	(Real / Integer / Nominal)	(0 / 5 / 0)
Instances	151	Classes	3
Missing values?			No

Attribute description

Attribute	Domain
Native	[1, 2]
Instructor	[1, 25]
Course	[1, 26]
Semester	[1, 2]
Size	[3, 66]
Class	{1, 2, 3}

Additional information

The data consist of evaluations of teaching performance over three regular semesters and two summer semesters of 151 teaching assistant (TA) assignments at the Statistics Department of the University of Wisconsin-Madison. The scores were divided into 3 roughly equal-sized categories (low (1), medium (2), and high (3)) to form the class variable.

Attributes description:

1. Native -> whether of not the TA is a native English speaker: 1 = English speaker, 2 = non-English speaker.
2. Instructor -> course instructor (25 categories).
3. Course -> 26 categories.
4. Semester -> summer or regular semester: 1 = Summer, 2 = Regular.
5. Size -> class size (numerical).

Files and additional references

In this section you can download some files related to the tae 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/Teaching+Assistant+Evaluation.