Search Results - "Calders, T."

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  1. 1

    Axiomatization of frequent itemsets by Calders, T., Paredaens, J.

    Published in Theoretical computer science (2003)
    “…Mining association rules is very popular in the data mining community. Most algorithms designed for finding association rules start with searching for frequent…”
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    Journal Article
  2. 2

    Applying Webmining techniques to execution traces to support the program comprehension process by Zaidman, A., Calders, T., Demeyer, S., Paredaens, J.

    “…Well-designed object-oriented programs typically consist of a few key classes that work tightly together to provide the bulk of the functionality. As such,…”
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    Conference Proceeding
  3. 3

    Building Classifiers with Independency Constraints by Calders, T., Kamiran, F., Pechenizkiy, M.

    “…In this paper we study the problem of classifier learning where the input data contains unjustified dependencies between some data attributes and the class…”
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    Conference Proceeding
  4. 4

    Handling Conditional Discrimination by Zliobaite, I., Kamiran, F., Calders, T.

    “…Historical data used for supervised learning may contain discrimination. We study how to train classifiers on such data, so that they are discrimination free…”
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    Conference Proceeding
  5. 5

    Mining Views: Database Views for Data Mining by Blockeel, H., Calders, T., Fromont, E., Goethals, B.

    “…We present a system towards the integration of data mining into relational databases. To this end, a relational database model is proposed, based on the so…”
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    Conference Proceeding
  6. 6

    Classifying without discriminating by Kamiran, F., Calders, T.

    “…Classification models usually make predictions on the basis of training data. If the training data is biased towards certain groups or classes of objects,…”
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    Conference Proceeding
  7. 7

    Mining Frequent Itemsets in a Stream by Calders, T., Dexters, N., Goethals, B.

    “…We study the problem of finding frequent itemsets in a continuous stream of transactions. The current frequency of an itemset in a stream is defined as its…”
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    Conference Proceeding
  8. 8

    Anti-monotonic Overlap-Graph Support Measures by Calders, T., Ramon, J., Van Dyck, D.

    “…In graph mining, a frequency measure is anti-monotonic if the frequency of a pattern never exceeds the frequency of a subpattern. The efficiency and…”
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    Conference Proceeding
  9. 9

    Workshop on Educational Data Mining @ ICALT07 (EDM@ICALT07) by Beck, J.E., Calders, T., Pechenizkiy, M., Viola, S.R.

    “…The educational data mining workshop1 held in conjunction with the 7 IEEE International Conference on Advanced Learning Technologies (ICALT) in Niigata, Japan…”
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    Conference Proceeding
  10. 10

    The Impact of Peripheral Neuropathy and Cognitive Decrements on Gait in Older Adults With Type 2 Diabetes Mellitus by Roman de Mettelinge, Tine, MSc, Delbaere, Kim, PT, PhD, Calders, Patrick, PT, PhD, Gysel, Tineke, MSc, Van Den Noortgate, Nele, MD, PhD, Cambier, Dirk, PT, PhD

    “…Abstract Objective To investigate the effect of peripheral neuropathy and cognition on gait performance in older adults with type 2 diabetes mellitus. Design…”
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    Journal Article