Two simulated data sets, with and without noise. Each record represents 100 points on a twodimensional graph, where the algorithm must classify the series as either a Hill (a “bump” in the terrain) or a Valley (a “dip” in the terrain)
Hill_Valley_with_noise_Training.data (417.4KB)
Hill_Valley_with_noise_Testing.data (420.9KB)
Hill_Valley_without_noise_Training.data (722.7KB)
Hill_Valley_without_noise_Testing.data (722.8KB)
This is NOT a manufacturing dataset, but looks good for testing pattern detection methods.
| Data Set Characteristics | Attribute Characteristics | Associated Tasks |
|---|---|---|
| Sequential | Real | Classification |
| Number of Instances | Number of Attributes | Number of Classes | |
|---|---|---|---|
| 1212 | 101 | 2 |
feature : V1~V100, Class
-
100 predictive attributes, 1 goal attribute
-
1-100 : Labeled x##. Floating point values (numeric)
-
101 : Labeled class. Binary {0,1} representing {valley,hill} (nominal)
number of instance
- training 606, test 606
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 (class distribution : 305/301)
(b) Hill_Valley_without_noise_Testing.data (295/311)
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 (307/299)
(d) Hill_Valley_with_noise_Testing.data (299/307)
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.
1~100 is numeric, class is {0,1}
(f) Hill_Valley_visual_examples.jpg
This graphic file shows two example instances from the data.
- Example of 'valley' instance from Hill-Valley without noise
- Example of 'hill' instance from Hill-Valley dataset with noise
1-100: Labeled “X##”. Floating point values (numeric) 101: Labeled “class”. Binary {0, 1} representing {valley, hill}
task : supervised classification on hill-valley
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https://www.simonwenkel.com/2018/08/19/revisiting_ml_hill_valley_detection.html