Contrast data mining : concepts, algorithms, and - download pdf or read online

February 2, 2018 | Data Mining | By admin | 0 Comments

By Guozhu Dong, James Bailey

ISBN-10: 1439854327

ISBN-13: 9781439854327

''Preface Contrasting is among the most simple kinds of research. Contrasting established research is normally hired, frequently subconsciously, by means of every kind of individuals. humans use contrasting to raised comprehend the area round them and the difficult difficulties they wish to unravel. humans use contrasting to competently examine the desirability of significant occasions, and to assist them larger keep away from very likely harmful Read more...

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Example text

An itemset is a finite set of items. A transaction t is said to satisfy or match an itemset X if X ⊆ t. Preliminaries 7 When vector data is discretized, the itemset concept carries over. Recall that the form of an item here is either A = a or A ∈ a, depending on whether A is categorical or numerical. The satisfaction of an item A = a or A ∈ a by a vector t is defined in the natural manner. A vector t satisfies an itemset X if each item in X is satisfied by t. Equivalently, we say that t satisfies an itemset X if the discretized version of t satisfies X in the transaction sense.

4 13 14 15 18 19 20 An important task when working with contrast patterns is the assessment of their quality or discriminative ability. In this chapter, we review a range of measures that may be used to assess the discriminative ability of contrast patterns. Some of these measures have their origins in association rules, others in statistics, and others in subgroup discovery. Our presentation is not exhaustive, since dozens of measures exist. Instead we present a selection that covers a number of the main types.

Signal to Noise Ratio: This is popular in the area of gene expression analysis [374]: |μDp − μDn | SN R = σDp + σDn where μDi is the mean value of the contrast feature in Di and σDi is its standard deviation. If the difference between the two means is large and the measure of variability (the denominator) is small, this indicates stronger discrimination or contrast. Area under the ROC Curve (AUC): This views the contrast feature value as a ranking measure and assesses whether the instances in Dp tend to be ranked higher than those in Dn .

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Contrast data mining : concepts, algorithms, and applications by Guozhu Dong, James Bailey


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