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Internet-Advertisements

Internet-Advertisements

deactivated ARFF Publicly available Visibility: public Uploaded 30-10-2014 by Joaquin Vanschoren
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  • OpenML100 study_123 study_14 study_34
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Author: Nicholas Kushmerick Source: [UCI](http://archive.ics.uci.edu/ml/datasets/Internet+Advertisements) - 1998 Please cite: ### Description This dataset represents a set of possible advertisements on Internet pages ### Sources (a) Creator and donor: Nicholas Kushmerick - nick@ucd.ie ### Dataset Information The features encode the geometry of the image (if available) as well as phrases occurring in the URL, the image's URL and alt text, the anchor text, and words occurring near the anchor text. The task is to predict whether an image is an advertisement ("ad") or not ("nonad"). ### Atributtes Information There are : 3 continuous attributes. The others are binary. This is the "STANDARD encoding" mentioned in the [Kushmerick, 99] (see below). One or more of the three continuous features are missing in 28% of the instances. Missing values should be interpreted as "unknown". ### Relevant Papers N. Kushmerick (1999). "Learning to remove Internet advertisements", 3rd Int Conf Autonomous Agents. Available at: http://rexa.info/paper/2fdc1cee89b7f4f2c9227d6f5d9b05d22c5ab3e9

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30 tasks

57663 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: class
25422 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: area_under_roc_curve - target_feature: class
12645 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: precision - target_feature: class
0 runs - estimation_procedure: 33% Holdout set - evaluation_measure: predictive_accuracy - target_feature: class
81 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
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0 runs - estimation_procedure: Interleaved Test then Train - target_feature: class
0 runs - estimation_procedure: 50 times Clustering
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0 runs - estimation_procedure: 50 times Clustering
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0 runs - estimation_procedure: 50 times Clustering
0 runs - target_feature: class
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0 runs - estimation_procedure: 50 times Clustering
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0 runs - estimation_procedure: 50 times Clustering
1304 runs - target_feature: class
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