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visualizing_galaxy

visualizing_galaxy

active ARFF Publicly available Visibility: public Uploaded 04-10-2014 by Joaquin Vanschoren
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Author: Source: Unknown - Date unknown Please cite: This S dump contains 22 data sets from the book Visualizing Data published by Hobart Press (books@hobart.com). The dump was created by data.dump() and can be read back into S by data.restore(). The name of each S data set is the name of the data set used in the book. To find the description of the data set in the book look under the entry - data, name - in the index. For example, one data set is barley. To find the description of barley, look in the index under the entry - data, barley. File: ../data/visualizing/galaxy.csv Information about the dataset CLASSTYPE: numeric CLASSINDEX: none specific

5 features

velocity (target)numeric208 unique values
0 missing
eastwestnumeric323 unique values
0 missing
northsouthnumeric323 unique values
0 missing
anglenumeric7 unique values
0 missing
radialpositionnumeric323 unique values
0 missing

19 properties

323
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.
-15.89
Average class difference between consecutive instances.
0
Percentage of missing values.
0.02
Number of attributes divided by the number of instances.
100
Percentage of numeric attributes.
Percentage of instances belonging to the most frequent class.
0
Percentage of nominal attributes.
Number of instances belonging to the most frequent class.
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.

15 tasks

0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: mean_absolute_error - target_feature: velocity
0 runs - estimation_procedure: Leave one out - evaluation_measure: predictive_accuracy - target_feature: velocity
0 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: velocity
0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: mean_absolute_error - target_feature: velocity
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
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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