Data
volcanoes-d4

volcanoes-d4

active ARFF Publicly available Visibility: public Uploaded 01-06-2015 by Rafael G. Mantovani
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Author: Michael C. Burl Source: UCI Please cite: * Dataset Title: Volcanoes on Venus - JARtool experiment Data Set Experiment: D4 * Source: Michael C. Burl MS 126-347, JPL 4800 Oak Grove Drive Pasadena, CA 91109 (818) 393-5345 Michael.C.Burl '@' jpl.nasa.gov http://www-aig.jpl.nasa.gov/mls/home/burl/ * Data Set Information: The data was collected by the Magellan spacecraft over an approximately four year period from 1990--1994. The objective of the mission was to obtain global mapping of the surface of Venus using synthetic aperture radar (SAR). A more detailed discussion of the mission and objectives is available at JPL's Magellan webpage. There are some spatial dependencies. For example, background patches from with in a single image are likely to be more similar than background patches taken across different images. In addition to the images, there are "ground truth" files that specify the locations of volcanoes within the images. The quotes around "ground truth" are intended as a reminder that there is no absolute ground truth for this data set. No one has been to Venus and the image quality does not permit 100%, unambiguous identification of the volcanoes, even by human experts. There are labels that provide some measure of subjective uncertainty (1 = definitely a volcano, 2 = probably, 3 = possibly, 4 = only a pit is visible). See reference [Smyth95] for more information on the labeling uncertainty problem. There are also files that specify the exact set of experiments using in the published evaluations of the JARtool system. * Attribute Information: The images are 1024X1024 pixels. The pixel values are in the range [0,255]. The pixel value is related to the amount of energy backscattered to the radar from a given spatial location. Higher pixel values indicate greater backscatter. Lower pixel values indicate lesser backscatter. Both topography and surface roughness relative to the radar wavelength affect the amount of backscatter. * Relevant Papers: G.H. Pettengill, P.G. Ford, W.T.K. Johnson, R.K. Raney, L.A. Soderblom, "Magellan: Radar Performance and Data Products", Science, 252:260-265 (1991). R.S. Saunders, A.J. Spear, P.C. Allin, R.S. Austin, A.L. Berman, R.C. Chandlee, J. Clark, A.V. Decharon, E.M. Dejong, "Magellan Mission Summary", J. of Geophysical Research Planets, 97(E8):13067-13090, (1992). M.C. Burl, L. Asker, P. Smyth, U. Fayyad, P. Perona, L. Crumpler, and J. Aubele, "Learning to Recognize Volcanoes on Venus", Machine Learning, (March 1998). P. Smyth, M.C. Burl, U.M. Fayyad, and P. Perona, Chapter: "Knowledge Discovery in Large Image Databases: Dealing with Uncertainties in Ground Truth", In Advances in Knowledge Discovery and Data Mining, AAAI/MIT Press, Menlo Park, CA, (1995).

4 features

Class (target)nominal5 unique values
0 missing
V1numeric992 unique values
0 missing
V2numeric993 unique values
0 missing
V3numeric8484 unique values
0 missing

62 properties

8654
Number of instances (rows) of the dataset.
4
Number of attributes (columns) of the dataset.
5
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.
3
Number of numeric attributes.
1
Number of nominal attributes.
0
Percentage of binary attributes.
288.13
Second quartile (Median) of standard deviation of attributes of the numeric type.
Maximum entropy among attributes.
-1.21
Minimum kurtosis among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
1.45
Maximum kurtosis among attributes of the numeric type.
0.45
Minimum of means among attributes of the numeric type.
0
Percentage of missing values.
1.45
Third quartile of kurtosis among attributes of the numeric type.
506.85
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
75
Percentage of numeric attributes.
506.85
Third quartile of means among attributes of the numeric type.
Maximum mutual information between the nominal attributes and the target attribute.
5
The minimal number of distinct values among attributes of the nominal type.
25
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
5
The maximum number of distinct values among attributes of the nominal type.
-0
Minimum skewness among attributes of the numeric type.
First quartile of entropy among attributes.
1.23
Third quartile of skewness among attributes of the numeric type.
1.23
Maximum skewness among attributes of the numeric type.
0.09
Minimum standard deviation of attributes of the numeric type.
-1.21
First quartile of kurtosis among attributes of the numeric type.
288.18
Third quartile of standard deviation of attributes of the numeric type.
288.18
Maximum standard deviation of attributes of the numeric type.
0.65
Percentage of instances belonging to the least frequent class.
0.45
First quartile of means among attributes of the numeric type.
0
Standard deviation of the number of distinct values among attributes of the nominal type.
Average entropy of the attributes.
56
Number of instances belonging to the least frequent class.
First quartile of mutual information between the nominal attributes and the target attribute.
-0.31
Mean kurtosis among attributes of the numeric type.
0
Number of binary attributes.
-0
First quartile of skewness among attributes of the numeric type.
337.8
Mean of means among attributes of the numeric type.
0.09
First quartile of standard deviation of attributes of the numeric type.
0.97
Average class difference between consecutive instances.
Average mutual information between the nominal attributes and the target attribute.
Second quartile (Median) of entropy among attributes.
0.42
Entropy of the target attribute values.
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
-1.18
Second quartile (Median) of kurtosis among attributes of the numeric type.
0
Number of attributes divided by the number of instances.
5
Average number of distinct values among the attributes of the nominal type.
506.1
Second quartile (Median) of means among attributes of the numeric type.
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
0.42
Mean skewness among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
94.33
Percentage of instances belonging to the most frequent class.
192.13
Mean standard deviation of attributes of the numeric type.
0.02
Second quartile (Median) of skewness among attributes of the numeric type.
8163
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.

4 tasks

89 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: Class
32 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: Class
0 runs - estimation_procedure: 50 times Clustering
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