Data
laser

laser

active ARFF Public Domain (CC0) Visibility: public Uploaded 19-04-2020 by Rafael Gomes Mantovani
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Author: Source: KEEL - [original](https://sci2s.ugr.es/keel/dataset.php?cod=47) - Date unknown Please cite: Laser generated dataset This data set was originally a univariate time record of a single observed quantity, recorded from a Far-Infrared-Laser in a chaotic state. The original set 1000 points has been adapted for regression by considering every set of four consecutive values as inputs, and the next one as output. Duplicated instances has been removed.

5 features

Output (target)numeric191 unique values
0 missing
Input1numeric189 unique values
0 missing
Input2numeric190 unique values
0 missing
Input3numeric190 unique values
0 missing
Input4numeric190 unique values
0 missing

19 properties

993
Number of instances (rows) of the dataset.
5
Number of attributes (columns) of the dataset.
0
Number of distinct values of the target attribute (if it is nominal).
0
Number of missing values in the dataset.
0
Number of instances with at least one value missing.
5
Number of numeric attributes.
0
Number of nominal attributes.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the least frequent class.
0
Number of binary attributes.
0
Percentage of binary attributes.
0
Percentage of instances having missing values.
0
Percentage of missing values.
-38.53
Average class difference between consecutive instances.
100
Percentage of numeric attributes.
0.01
Number of attributes divided by the number of instances.
0
Percentage of nominal attributes.
Percentage of instances belonging to the most frequent class.
Number of instances belonging to the most frequent class.

9 tasks

0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: mean_absolute_error - target_feature: Output
0 runs - estimation_procedure: 33% Holdout set - target_feature: Output
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
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