Lee Graham (lee '@' stellaralchemy.com)

Franz Oppacher (oppacher '@' scs.carleton.ca)
Carleton University, Department of Computer Science
Intelligent Systems Research Unit
1125 Colonel By Drive, Ottawa, Ontario, Canada, K1S5B6

Data Set Information:

Each record represents 100 points on a two-dimensional graph. When plotted in order (from 1 through 100) as the Y co-ordinate, the points will create either a Hill (a “bump” in the terrain) or a Valley (a “dip” in the terrain).

There are six files, as follows:

(a) Hill_Valley_without_noise_Training.data
(b) Hill_Valley_without_noise_Testing.data

These first two datasets (without noise) are a training/testing set pair where the hills or valleys have a smooth transition.

(c) Hill_Valley_with_noise_Training.data
(d) Hill_Valley_with_noise_Testing.data

These next two datasets (with noise) are a training/testing set pair where the terrain is uneven, and the hill or valley is not as obvious when viewed closely.

(e) Hill_Valley_sample_arff.text

The sample ARFF file is useful for setting up experiments, but is not necessary.

(f) Hill_Valley_visual_examples.jpg

This graphic file shows two example instances from the data.

Attribute Information:

1-100: Labeled “X##”. Floating point values (numeric)
101: Labeled “class”. Binary {0, 1} representing {valley, hill}

Relevant Papers:

1. Non-published. evaluation of dataset by various learning algorithms in the Waikato Environment for Knowledge Analysis (WEKA).

Citation Request:

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