Advances in Data Mining. Applications and Theoretical by Hongmin Cai (auth.), Petra Perner (eds.)

By Hongmin Cai (auth.), Petra Perner (eds.)

This ebook constitutes the refereed complaints of the eleventh business convention on information Mining, ICDM 2011, held in long island, united states in September 2011.

The 22 revised complete papers offered have been rigorously reviewed and chosen from a hundred submissions. The papers are geared up in topical sections on information mining in medication and agriculture, facts mining in advertising, info mining for business approaches and in telecommunication, Multimedia information Mining, theoretical facets of information mining, info Warehousing, WebMining and knowledge Mining.

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N}) φi(v[n+2]) = |ei[n+2]Tv[n+2]| = |wi| (41) where ei[n+2] are the unit vectors and v[n+2] = [w[n]T, θ, β]T. The modified CPL criterion function ΨH(v[n+1]) has the below form [9]: ΨH(v[n+2]) = ΦH(v[n+2]) + λ Σ γi φi (v[n+2]) i ∈{1,…,n} (42) where λ (λ ≥ 0) is the cost level and the feature costs γi are typically equal to one. The criterion function ΨH(v[n+2) (42) similarly to the function ΦH(v[n+2]) (32) is convex and piecewise-linear (CPL). , wλn*]T (22). (43) Prognostic Models Based on Linear Separability 21 The optimal vector vλ*[n+2] (43) allows to define both the interval regression model (4) as well as the below decision rule of the linear classifier which operates on elements of the sets H+ or H- (25) (z[n+2] = zj+[n+2] or z[n+2] = zj-[n+2] (21)).

We can remark, that such features xi which have the weights wλi* equal to zero (wλi* = 0) in the optimal vector vλ*[n+2] (43) can be reduced without changing the decision rule (44). The weights wλi* equal to zero (wλi* = 0) does not change also the decision rule (47. The below feature reduction rule has been proposed basing on this property [10]: (wλi* = 0) ⇒ (the feature xi is reduced) (50) In accordance with the relaxed linear separability (RLS) method of feature subsets selection, a successive increase of the cost level λ in the minimized criterion function ΨH(v[n+2) (42) or the criterion function ΨR(w[n]) (45) reduces more weights wλi* to zero (wλi* = 0) and, in result, reduces additional features xi (49).

PhD Thesis, TU Delft (2001) 10. : Support objects for domain approximation. In: ICANN, Skovde, Sweden (1998) How to Interpret Decision Trees? de Abstract. Data mining methods are widely used across many disciplines to identify patterns, rules or associations among huge volumes of data. While in the past mostly black box methods such as neural nets and support vector machines have been heavily used in technical domains, methods that have explanation capability are preferred in medical domains. Nowadays, data mining methods with explanation capability are also used for technical domains after more work on advantages and disadvantages of the methods has been done.

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