Data
dbworld-subjects-stemmed

dbworld-subjects-stemmed

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Author: Michele Filannino Source: UCI Please cite: * Dataset: DBworld e-mails data set Task: dbworld-subjects-stemmed * Source: Michele Filannino, PhD University of Manchester Centre for Doctoral Training Email: filannim_AT_cs.man.ac.uk * Data Set Information: I collected 64 e-mails from DBWorld newsletter and I used them to train different algorithms in order to classify between 'announces of conferences' and 'everything else'. I used a binary bag-of-words representation with a stopword removal pre-processing task before. * Attribute Information: Each attribute corresponds to a precise word or stem in the entire data set vocabulary (I used bag-of-words representation). * Relevant Papers: Michele Filannino, 'DBWorld e-mail classification using a very small corpus', Project of Machine Learning course, University of Manchester, 2011.

230 features

Class (target)nominal2 unique values
0 missing
V1nominal2 unique values
0 missing
V2nominal2 unique values
0 missing
V3nominal2 unique values
0 missing
V4nominal2 unique values
0 missing
V5nominal2 unique values
0 missing
V6nominal2 unique values
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V7nominal2 unique values
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V8nominal2 unique values
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V9nominal2 unique values
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V10nominal2 unique values
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V11nominal2 unique values
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V12nominal2 unique values
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V13nominal2 unique values
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V14nominal2 unique values
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V15nominal2 unique values
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V16nominal2 unique values
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V17nominal2 unique values
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V18nominal2 unique values
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V19nominal2 unique values
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V20nominal2 unique values
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V21nominal2 unique values
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V22nominal2 unique values
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V23nominal2 unique values
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V24nominal2 unique values
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V25nominal2 unique values
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V26nominal2 unique values
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V27nominal2 unique values
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V28nominal2 unique values
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V29nominal2 unique values
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V30nominal2 unique values
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V31nominal2 unique values
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V32nominal2 unique values
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V33nominal2 unique values
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V34nominal2 unique values
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V35nominal2 unique values
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V36nominal2 unique values
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V37nominal2 unique values
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V38nominal2 unique values
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V39nominal2 unique values
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V40nominal2 unique values
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V41nominal2 unique values
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V42nominal2 unique values
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V43nominal2 unique values
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V44nominal2 unique values
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V45nominal2 unique values
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V46nominal2 unique values
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V47nominal2 unique values
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V48nominal2 unique values
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V49nominal2 unique values
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V51nominal2 unique values
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V53nominal2 unique values
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V56nominal2 unique values
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V58nominal2 unique values
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V59nominal2 unique values
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V60nominal2 unique values
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V61nominal2 unique values
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V62nominal2 unique values
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V63nominal2 unique values
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V64nominal2 unique values
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V65nominal2 unique values
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V66nominal2 unique values
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V67nominal2 unique values
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V68nominal2 unique values
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V69nominal2 unique values
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V70nominal2 unique values
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V71nominal2 unique values
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V72nominal2 unique values
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V73nominal2 unique values
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V74nominal2 unique values
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V75nominal2 unique values
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V76nominal2 unique values
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V77nominal2 unique values
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V78nominal2 unique values
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V79nominal2 unique values
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V80nominal2 unique values
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V81nominal2 unique values
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V82nominal2 unique values
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V83nominal2 unique values
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V84nominal2 unique values
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V85nominal2 unique values
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V86nominal2 unique values
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V87nominal2 unique values
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V88nominal2 unique values
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V89nominal2 unique values
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V90nominal2 unique values
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V91nominal2 unique values
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V92nominal2 unique values
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V93nominal2 unique values
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V94nominal2 unique values
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V95nominal2 unique values
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V96nominal2 unique values
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V98nominal2 unique values
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V99nominal2 unique values
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V100nominal2 unique values
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V101nominal2 unique values
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V102nominal2 unique values
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V103nominal2 unique values
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V104nominal2 unique values
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V105nominal2 unique values
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V106nominal2 unique values
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V107nominal2 unique values
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V108nominal2 unique values
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V109nominal2 unique values
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V110nominal2 unique values
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V111nominal2 unique values
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V112nominal2 unique values
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V113nominal2 unique values
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V114nominal2 unique values
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V115nominal2 unique values
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V116nominal2 unique values
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V117nominal2 unique values
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V118nominal2 unique values
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V119nominal2 unique values
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V120nominal2 unique values
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V121nominal2 unique values
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V122nominal2 unique values
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V123nominal2 unique values
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V124nominal2 unique values
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V125nominal2 unique values
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V126nominal2 unique values
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V127nominal2 unique values
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V128nominal2 unique values
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V129nominal2 unique values
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V130nominal2 unique values
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V131nominal2 unique values
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V132nominal2 unique values
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V133nominal2 unique values
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V134nominal2 unique values
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V135nominal2 unique values
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V136nominal2 unique values
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V137nominal2 unique values
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V138nominal2 unique values
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V141nominal2 unique values
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V142nominal2 unique values
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V146nominal2 unique values
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V147nominal2 unique values
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V148nominal2 unique values
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V150nominal2 unique values
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V151nominal2 unique values
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V160nominal2 unique values
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V161nominal2 unique values
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V162nominal2 unique values
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V163nominal2 unique values
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V164nominal2 unique values
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V165nominal2 unique values
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V166nominal2 unique values
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V168nominal2 unique values
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V174nominal2 unique values
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V176nominal2 unique values
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V177nominal2 unique values
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V178nominal2 unique values
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V179nominal2 unique values
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V180nominal2 unique values
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V181nominal2 unique values
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V182nominal2 unique values
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V183nominal2 unique values
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V184nominal2 unique values
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V185nominal2 unique values
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V186nominal2 unique values
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V187nominal2 unique values
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V188nominal2 unique values
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V189nominal2 unique values
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V190nominal2 unique values
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V191nominal2 unique values
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V192nominal2 unique values
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V193nominal2 unique values
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V194nominal2 unique values
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V195nominal2 unique values
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V196nominal2 unique values
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V197nominal2 unique values
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V198nominal2 unique values
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V199nominal2 unique values
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V200nominal2 unique values
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V201nominal2 unique values
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V202nominal2 unique values
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V203nominal2 unique values
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V204nominal2 unique values
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V205nominal2 unique values
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V206nominal2 unique values
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V207nominal2 unique values
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V208nominal2 unique values
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V209nominal2 unique values
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V210nominal2 unique values
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V211nominal2 unique values
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V212nominal2 unique values
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V213nominal2 unique values
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V214nominal2 unique values
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V215nominal2 unique values
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V216nominal2 unique values
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V217nominal2 unique values
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V218nominal2 unique values
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V219nominal2 unique values
0 missing
V220nominal2 unique values
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V221nominal2 unique values
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V222nominal2 unique values
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V223nominal2 unique values
0 missing
V224nominal2 unique values
0 missing
V225nominal2 unique values
0 missing
V226nominal2 unique values
0 missing
V227nominal2 unique values
0 missing
V228nominal2 unique values
0 missing
V229nominal2 unique values
0 missing

62 properties

64
Number of instances (rows) of the dataset.
230
Number of attributes (columns) of the dataset.
2
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.
0
Number of numeric attributes.
230
Number of nominal attributes.
First quartile of skewness among attributes of the numeric type.
Mean of means among attributes of the numeric type.
First quartile of standard deviation of attributes of the numeric type.
0.94
Average class difference between consecutive instances.
0.02
Average mutual information between the nominal attributes and the target attribute.
0.12
Second quartile (Median) of entropy among attributes.
0.99
Entropy of the target attribute values.
6.56
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
Second quartile (Median) of kurtosis among attributes of the numeric type.
3.59
Number of attributes divided by the number of instances.
2
Average number of distinct values among the attributes of the nominal type.
Second quartile (Median) of means among attributes of the numeric type.
44.56
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
Mean skewness among attributes of the numeric type.
0.02
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
54.69
Percentage of instances belonging to the most frequent class.
Mean standard deviation of attributes of the numeric type.
Second quartile (Median) of skewness among attributes of the numeric type.
35
Number of instances belonging to the most frequent class.
0.12
Minimal entropy among attributes.
100
Percentage of binary attributes.
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.84
Maximum entropy among attributes.
Minimum kurtosis among attributes of the numeric type.
0
Percentage of instances having missing values.
0.2
Third quartile of entropy among attributes.
Maximum kurtosis among attributes of the numeric type.
Minimum of means among attributes of the numeric type.
0
Percentage of missing values.
Third quartile of kurtosis among attributes of the numeric type.
Maximum of means among attributes of the numeric type.
0
Minimal mutual information between the nominal attributes and the target attribute.
0
Percentage of numeric attributes.
Third quartile of means among attributes of the numeric type.
0.29
Maximum mutual information between the nominal attributes and the target attribute.
2
The minimal number of distinct values among attributes of the nominal type.
100
Percentage of nominal attributes.
0.02
Third quartile of mutual information between the nominal attributes and the target attribute.
2
The maximum number of distinct values among attributes of the nominal type.
Minimum skewness among attributes of the numeric type.
0.12
First quartile of entropy among attributes.
Third quartile of skewness among attributes of the numeric type.
Maximum skewness among attributes of the numeric type.
Minimum standard deviation of attributes of the numeric type.
First quartile of kurtosis among attributes of the numeric type.
Third quartile of standard deviation of attributes of the numeric type.
Maximum standard deviation of attributes of the numeric type.
45.31
Percentage of instances belonging to the least frequent class.
29
Number of instances belonging to the least frequent class.
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.
0.17
Average entropy of the attributes.
230
Number of binary attributes.
0.01
First quartile of mutual information between the nominal attributes and the target attribute.
Mean kurtosis among attributes of the numeric type.

5 tasks

40 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: Class
31 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: Class
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
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