资源介绍
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:
Please refer to the Machine Learning Repository's citation policy
