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Click_prediction_small

active ARFF Publicly available Visibility: public Uploaded 23-11-2014 by unknown
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Author: Source: Unknown - Date unknown Please cite: Data on predicting clicks on ads in a search engine.

10 features

click (target)	nominal	2 unique values 0 missing
impression	numeric	389 unique values 0 missing
url_hash (ignore)	numeric	19727 unique values 0 missing
ad_id	numeric	159955 unique values 0 missing
advertiser_id	numeric	13646 unique values 0 missing
depth	numeric	3 unique values 0 missing
position	numeric	3 unique values 0 missing
query_id (ignore)	numeric	822185 unique values 0 missing
keyword_id	numeric	196000 unique values 0 missing
title_id	numeric	386492 unique values 0 missing
description_id	numeric	315255 unique values 0 missing
user_id	numeric	976977 unique values 0 missing

Show all 10 features

107 properties

NumberOfInstances

1496391

Number of instances (rows) of the dataset.

NumberOfFeatures

Number of attributes (columns) of the dataset.

NumberOfClasses

Number of distinct values of the target attribute (if it is nominal).

NumberOfMissingValues

Number of missing values in the dataset.

NumberOfInstancesWithMissingValues

Number of instances with at least one value missing.

NumberOfNumericFeatures

Number of numeric attributes.

NumberOfSymbolicFeatures

Number of nominal attributes.

AutoCorrelation

0.91

Average class difference between consecutive instances.

CfsSubsetEval_DecisionStumpAUC

0.52

Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W

CfsSubsetEval_DecisionStumpErrRate

0.04

Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W

CfsSubsetEval_DecisionStumpKappa

0.01

Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W

CfsSubsetEval_NaiveBayesAUC

0.52

Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W

CfsSubsetEval_NaiveBayesErrRate

0.04

Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W

CfsSubsetEval_NaiveBayesKappa

0.01

Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W

CfsSubsetEval_kNN1NAUC

0.52

Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W

CfsSubsetEval_kNN1NErrRate

0.04

Error rate achieved by the landmarker weka.classifiers.lazy.IBk -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W

CfsSubsetEval_kNN1NKappa

0.01

Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W

ClassEntropy

0.26

Entropy of the target attribute values.

DecisionStumpAUC

0.58

Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump

DecisionStumpErrRate

0.04

Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump

DecisionStumpKappa

Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump

Dimensionality

Number of attributes divided by the number of instances.

EquivalentNumberOfAtts

Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.

J48.00001.AUC

0.52

Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001

J48.00001.ErrRate

0.04

Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001

J48.00001.Kappa

0.01

Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001

J48.0001.AUC

0.52

Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001

J48.0001.ErrRate

0.04

Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001

J48.0001.Kappa

0.01

Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001

J48.001.AUC

0.52

Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001

J48.001.ErrRate

0.04

Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001

J48.001.Kappa

0.01

Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001

MajorityClassPercentage

95.54

Percentage of instances belonging to the most frequent class.

MajorityClassSize

1429610

Number of instances belonging to the most frequent class.

MaxAttributeEntropy

Maximum entropy among attributes.

MaxKurtosisOfNumericAtts

740313.81

Maximum kurtosis among attributes of the numeric type.

MaxMeansOfNumericAtts

16009959.22

Maximum of means among attributes of the numeric type.

MaxMutualInformation

Maximum mutual information between the nominal attributes and the target attribute.

MaxNominalAttDistinctValues

The maximum number of distinct values among attributes of the nominal type.

MaxSkewnessOfNumericAtts

796.6

Maximum skewness among attributes of the numeric type.

MaxStdDevOfNumericAtts

7211223.22

Maximum standard deviation of attributes of the numeric type.

MeanAttributeEntropy

Average entropy of the attributes.

MeanKurtosisOfNumericAtts

82268.55

Mean kurtosis among attributes of the numeric type.

MeanMeansOfNumericAtts

2212173.58

Mean of means among attributes of the numeric type.

MeanMutualInformation

Average mutual information between the nominal attributes and the target attribute.

MeanNoiseToSignalRatio

An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.

MeanNominalAttDistinctValues

Average number of distinct values among the attributes of the nominal type.

MeanSkewnessOfNumericAtts

90.41

Mean skewness among attributes of the numeric type.

MeanStdDevOfNumericAtts

1502375.57

Mean standard deviation of attributes of the numeric type.

MinAttributeEntropy

Minimal entropy among attributes.

MinKurtosisOfNumericAtts

-1.08

Minimum kurtosis among attributes of the numeric type.

MinMeansOfNumericAtts

1.49

Minimum of means among attributes of the numeric type.

MinMutualInformation

Minimal mutual information between the nominal attributes and the target attribute.

MinNominalAttDistinctValues

The minimal number of distinct values among attributes of the nominal type.

MinSkewnessOfNumericAtts

-0.88

Minimum skewness among attributes of the numeric type.

MinStdDevOfNumericAtts

0.65

Minimum standard deviation of attributes of the numeric type.

MinorityClassPercentage

4.46

Percentage of instances belonging to the least frequent class.

MinorityClassSize

66781

Number of instances belonging to the least frequent class.

NaiveBayesAUC

0.58

Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes

NaiveBayesErrRate

0.06

Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes

NaiveBayesKappa

0.02

Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes

NumberOfBinaryFeatures

Number of binary attributes.

PercentageOfBinaryFeatures

Percentage of binary attributes.

PercentageOfInstancesWithMissingValues

Percentage of instances having missing values.

PercentageOfMissingValues

Percentage of missing values.

PercentageOfNumericFeatures

Percentage of numeric attributes.

PercentageOfSymbolicFeatures

Percentage of nominal attributes.

Quartile1AttributeEntropy

First quartile of entropy among attributes.

Quartile1KurtosisOfNumericAtts

-0.92

First quartile of kurtosis among attributes of the numeric type.

Quartile1MeansOfNumericAtts

1.79

First quartile of means among attributes of the numeric type.

Quartile1MutualInformation

First quartile of mutual information between the nominal attributes and the target attribute.

Quartile1SkewnessOfNumericAtts

-0.29

First quartile of skewness among attributes of the numeric type.

Quartile1StdDevOfNumericAtts

35.61

First quartile of standard deviation of attributes of the numeric type.

Quartile2AttributeEntropy

Second quartile (Median) of entropy among attributes.

Quartile2KurtosisOfNumericAtts

2.53

Second quartile (Median) of kurtosis among attributes of the numeric type.

Quartile2MeansOfNumericAtts

34122.28

Second quartile (Median) of means among attributes of the numeric type.

Quartile2MutualInformation

Second quartile (Median) of mutual information between the nominal attributes and the target attribute.

Quartile2SkewnessOfNumericAtts

1.81

Second quartile (Median) of skewness among attributes of the numeric type.

Quartile2StdDevOfNumericAtts

97432.89

Second quartile (Median) of standard deviation of attributes of the numeric type.

Quartile3AttributeEntropy

Third quartile of entropy among attributes.

Quartile3KurtosisOfNumericAtts

38.97

Third quartile of kurtosis among attributes of the numeric type.

Quartile3MeansOfNumericAtts

1867346.2

Third quartile of means among attributes of the numeric type.

Quartile3MutualInformation

Third quartile of mutual information between the nominal attributes and the target attribute.

Quartile3SkewnessOfNumericAtts

5.55

Third quartile of skewness among attributes of the numeric type.

Quartile3StdDevOfNumericAtts

2941250.87

Third quartile of standard deviation of attributes of the numeric type.

REPTreeDepth1AUC

0.67

Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1

REPTreeDepth1ErrRate

0.04

Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1

REPTreeDepth1Kappa

0.03

Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1

REPTreeDepth2AUC

0.67

Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2

REPTreeDepth2ErrRate

0.04

Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2

REPTreeDepth2Kappa

0.03

Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2

REPTreeDepth3AUC

0.67

Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3

REPTreeDepth3ErrRate

0.04

Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3

REPTreeDepth3Kappa

0.03

Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3

RandomTreeDepth1AUC

0.53

Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1

RandomTreeDepth1ErrRate

0.08

Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1

RandomTreeDepth1Kappa

0.06

Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1

RandomTreeDepth2AUC

0.53

Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2

RandomTreeDepth2ErrRate

0.08

Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2

RandomTreeDepth2Kappa

0.06

Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2

RandomTreeDepth3AUC

0.53

Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3

RandomTreeDepth3ErrRate

0.08

Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3

RandomTreeDepth3Kappa

0.06

Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3

StdvNominalAttDistinctValues

Standard deviation of the number of distinct values among attributes of the nominal type.

kNN1NAUC

0.53

Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk

kNN1NErrRate

0.08

Error rate achieved by the landmarker weka.classifiers.lazy.IBk

kNN1NKappa

0.04

Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk

Show all 107 properties

13 tasks

Supervised Classification on Click_prediction_small

0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: area_under_roc_curve - target_feature: click - cost matrix: [[1000,-10],[-100,0]]

Supervised Classification on Click_prediction_small

0 runs - estimation_procedure: 33% Holdout set - evaluation_measure: predictive_accuracy - target_feature: click

Clustering on Click_prediction_small

0 runs

Clustering on Click_prediction_small

0 runs - estimation_procedure: 50 times Clustering

Clustering on Click_prediction_small

0 runs - estimation_procedure: 50 times Clustering

Clustering on Click_prediction_small

0 runs - estimation_procedure: 50 times Clustering

Clustering on Click_prediction_small

0 runs - estimation_procedure: 50 times Clustering