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Olivetti_Faces

Olivetti_Faces

active ARFF Public Domain (CC0) Visibility: public Uploaded 14-05-2018 by Irfan Nur Afif
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Author: AT&T Laboratories Cambridge Source: http://www.cl.cam.ac.uk/research/dtg/attarchive/facedatabase.html - Date: 1992-1994 Please cite: This dataset contains a set of face images taken between April 1992 and April 1994 at AT&T Laboratories Cambridge. As described on the original website: There are ten different images of each of 40 distinct subjects. For some subjects, the images were taken at different times, varying the lighting, facial expressions (open / closed eyes, smiling / not smiling) and facial details (glasses / no glasses). All the images were taken against a dark homogeneous background with the subjects in an upright, frontal position (with tolerance for some side movement). The image is quantized to 256 grey levels and stored as unsigned 8-bit integers; the loader will convert these to floating point values on the interval [0, 1], which are easier to work with for many algorithms. The “target” for this database is an integer from 0 to 39 indicating the identity of the person pictured; however, with only 10 examples per class, this relatively small dataset is more interesting from an unsupervised or semi-supervised perspective. The original dataset consisted of 92 x 112, while the version available here consists of 64x64 images. When using these images, please give credit to AT&T Laboratories Cambridge.

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62 properties

400
Number of instances (rows) of the dataset.
4097
Number of attributes (columns) of the dataset.
40
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.
4096
Number of numeric attributes.
1
Number of nominal attributes.
-0.57
First quartile of skewness among attributes of the numeric type.
0.55
Mean of means among attributes of the numeric type.
0.12
First quartile of standard deviation of attributes of the numeric type.
0.9
Average class difference between consecutive instances.
Average mutual information between the nominal attributes and the target attribute.
Second quartile (Median) of entropy among attributes.
5.32
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.
-0.25
Second quartile (Median) of kurtosis among attributes of the numeric type.
10.24
Number of attributes divided by the number of instances.
40
Average number of distinct values among the attributes of the nominal type.
0.54
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.
-0.3
Mean skewness among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
2.5
Percentage of instances belonging to the most frequent class.
0.14
Mean standard deviation of attributes of the numeric type.
-0.24
Second quartile (Median) of skewness among attributes of the numeric type.
10
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
0
Percentage of binary attributes.
0.14
Second quartile (Median) of standard deviation of attributes of the numeric type.
Maximum entropy among attributes.
-1.1
Minimum kurtosis among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
4.88
Maximum kurtosis among attributes of the numeric type.
0.24
Minimum of means among attributes of the numeric type.
0
Percentage of missing values.
0.14
Third quartile of kurtosis among attributes of the numeric type.
0.75
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
99.98
Percentage of numeric attributes.
0.62
Third quartile of means among attributes of the numeric type.
Maximum mutual information between the nominal attributes and the target attribute.
40
The minimal number of distinct values among attributes of the nominal type.
0.02
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
40
The maximum number of distinct values among attributes of the nominal type.
-2.06
Minimum skewness among attributes of the numeric type.
First quartile of entropy among attributes.
0
Third quartile of skewness among attributes of the numeric type.
1.08
Maximum skewness among attributes of the numeric type.
0.09
Minimum standard deviation of attributes of the numeric type.
-0.49
First quartile of kurtosis among attributes of the numeric type.
0.15
Third quartile of standard deviation of attributes of the numeric type.
0.21
Maximum standard deviation of attributes of the numeric type.
2.5
Percentage of instances belonging to the least frequent class.
10
Number of instances belonging to the least frequent class.
0.48
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.
0
Number of binary attributes.
First quartile of mutual information between the nominal attributes and the target attribute.
0.02
Mean kurtosis among attributes of the numeric type.

5 tasks

53 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: Interleaved Test then Train - target_feature: class
0 runs - estimation_procedure: 50 times Clustering
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