Summary: 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).
| Parameter | Value |
|---|---|
| Name | Hill-Valley |
| Labeled | Yes |
| Time Series | No |
| Simulation | No |
| Missing Values | No |
| Dataset Characteristics | Sequential |
| Feature Type | Real |
| Associated Tasks | Classification |
| Number of Instances | 606 |
| Number of Features | 101 |
| Date Donated | 2008-03-19 |
| Source | UCI Machine Learning Repository |
Each record represents 100 points on a two-dimensional graph. When plotted in order (from 1 through 100) as the Y-coordinate, 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.
Classification, Feature representation, Graph data, Pattern recognition