'2a 21 2a 22' diaporamas de présentation

? V(d)=

How do we use this theory? For Dot Product gap based Clustering, we can hill-climb a kk below to a d that gives us the global maximum variance. Heuristically, higher variance means more prominent gaps. X o d=F d (X)=DPP d (X). d 1. x 1 o d. x 1 x 2 : x N. x 2 o d. =.

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Separate class R , class V using midpoints of means :. vom V. vom R. d-line. d. v 2. v 1. a. FAUST Classifier. P r =P (x o d)< a. P v =P (x o d) ? a. Set a = (m R +(m V -m R )/2) o d = (m R +m V )/2 o d ?. where D ? m R ?m V d=D/|D|.

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? V(d)=

X o d=F d (X)=DPP d (X). d 1. x 1 o d. x 1 x 2 : x N. x 2 o d. =. - ( ? j=1..n X j d j ) 2. = ? i=1..N ( ? j=1..n x i,j d j ) 2. x N o d. d n. V(d) ? VarDPP d (X)= (X o d) 2 - (X o d) 2. = ? i ( ? j x i,j d j ). - ( ? j X j d j ). ( ? k X k d k ).

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? V(d)=

X o d=F d (X)=DPP d (X). d 1. x 1 o d. x 1 x 2 : x N. x 2 o d. =. - ( ? j=1..n X j d j ) 2. = ? i=1..N ( ? j=1..n x i,j d j ) 2. x N o d. d n. V(d) ? VarDPP d (X)= (X o d) 2 - (X o d) 2. = ? i ( ? j x i,j d j ). - ( ? j X j d j ). ( ? k X k d k ).

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