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Z O R - M e t h o d s a n d M o d e l s o f O p e r a t io n s R e s e a rc h ( 19 9 2) 3 6 :5 1 7 - 5 4 5
N o v e l p p ro a ch es t o t h e D i s cr im i n a t io n P ro b l em
P . M a r c o t t e a n d G . S a v a r d 1
Abstract W e con sider the pro blem of determ ining a hype rplane that separates , as we l l as possible,
two f in i t e se t s o f po in t s i n R . We ana lyze two c r i t e r i a fo r j udg ing the qua l i t y o f a cand ida t e
hype rplane ( i ) the m axim al d is tance of a misclassit ied po int to th e hyperp lane ( i i ) the nu mb er o f
misc lassi fi ed po in t s . I n each case, we inves t iga t e t he com puta t iona l com plex i ty o f t he co r r espond ing
ma them at i ca l p rograms, g ive equ iva l en t f o rmula t ions , suggest so lu t ion a lgor i thms and p resen t
prel im inary nu me r ical results.
Key words Discr iminan t ana lys i s . Quadra t i c p rogramming . Complex i ty . I n t eger p rogramming .
Bi level programming.
Introduct ion
Co n s i d e r r a n d o m s am p l e s X {xi} i~1 an d Y --- J{Y } j ~s f ro m t w o d i s t i n c t p o p u -
l a t i o n s 3 f an d qr i n R (x i e 5 f, y J ~ q/ ) w i t h r e s p ec t iv e d i s t r i b u t i o n fu n c t i o n s F x
a n d F t . G i v e n a r a n d o m l y g e n e ra t e d v e c t o r z o r ig i n a t in g fr o m ei ther p o p u l a t i o n
5 ( o r qr s t a t i s ti c a l l i n ea r d i s c r i m i n an t an a l y s i s u s e s a h y p e r p l an e a s a t o o l t o
d ec i d e w h e t h e r z e &r o r z e qr n am e l y z e X i f z l ie s ab o v e t h e h y p e rp l an e an dz e qr i f z l ie s b e l o w t h e h y p e rp l an e . S t a t is t i c a l d i s c r i m i n an t an a l y s i s i s an
es t ab l i s h ed f i e ld o f s ta t i s t ic a l t h eo ry . I n i ts s i mp l e s t , l in ea r fo rm , i t co n s i s t s i n
d e t e r m i n i n g t h e b e s t h y p e r p l a n e , i . e . t h e h y p e r p l a n e t h a t m a x i m i z e s t h e p r o b -
a b i l i ty o f c o r r e c t l y a s si g n i n g z t o p o p u l a t i o n 5 f o r qr W h e n {x i} i~ i a n d J
a r e r a n d o m s a m p l e s d r a w n f r o m m u l t iv a r i a te n o r m a l p o p u l a t i o n s w i t h re s pe c ti ve
m e a n s / ~ x a n d # r a n d common v a r i a n c e - c o v a r i a n c e m a t r i x 2~, i t c a n b e s h o w n
t h a t t h e o p t i m a l h y p e rp l an e i s g i v en b y t h e fo rm u l a (s ee F i s h e r 1 4 ]):
p t z a = O
R e s e a rc h s u p p o r t e d b y N S E R C g r a n ts 5 7 8 9 a n d 4 64 05 , th e A c a d e m i c R e s e a rc h P r o g r a m o f t h e
De par tm en t o f Na t iona l D efense (Canada) and FC A R gran t 91NC0510 . (Quebec) .
1 P ro fesso r s Dr . Pa t r i ce M arco t t e and Gi l l e s Savard , Drp ar t em en t de M ath+mat iques , Co ll~ge
mi l i t a i re roya l de Sa in t -Jean , Riche la in Qurb ec J0J 1R0 , Cana da .
03 40 - 9422 /92 /6 /51 7- 545 $2.50 9 1992 Phys i ca -Ver lag , H e ide lberg
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518
w h e r e
P. M arcotte and G . Savard
P = L ' - l ( # x - # r )
a = - 5 ( x + r ) r - l ( ~ x - ~ r ) - I n
a n d p a n d 1 - p a r e p r i o r p ro b a b i l it i e s a s s ig n e d t o p o p u l a t i o n s Y a n d ~1
respec t ive ly .
I n t h i s p a p e r w e f o ll o w a n a l t o g e t h e r d i f f e re n t a p p r o a c h (se e a ls o C a v a l i e r e t
a l. [3 ] ). W e d o n o t a s s u m e a n y f u n c t i o n a l f o r m f o r t h e d i s t r ib u t i o n s F x a n d F t .A c t u a l l y w e d o n o t e v e n a s s u m e t h e p o i n t s x i a n d y J t o b e r a n d o m . R a t h e r w e
l o o k f o r a d i s c r i m i n a t i n g h y p e r p l a n e t h a t m a x i m i z e s a f u n c t i o n r e p r e s e n t i n g ,
i n a s en s e to b e d e t e rm i n ed , t h e l ev e l o f d i s c r i m i n a t i o n b e t w een t h e t w o s e t s X
and Y.
T h e p a p e r i s d i v i d e d i n t o t w o s y m m e t r i c p a r t s, e a c h d e v o t e d t o a m a t h e m a t i c a l
p r o g r a m m i n g m o d e l o f t h e d i s c r im i n a t i o n p r o bl e m . T h e p a p e r is en t ir e ly d e v o t e d
t o a l g o r i t h m s a n d d o e s n o t a d d r e s s t h e i m p o r t a n t , b u t o f a v e r y d if f e re n t n a t u r e ,
q u e s t io n o f t h e r e le v a n ce o f th e m a t h e m a t i c a l p r o g r a m m i n g a p p r o a c h o v er , sa y ,
t h e s t a ti s ti c a l a p p r o a c h t o t h e d i s c r i m i n a t i o n p r o b l e m .F o r e a c h m o d e l , w e a n a l y z e w o r s t- c a s e c o m p l e x i ty , gi ve r e la t e d f o r m u l a t i o n s ,
p r o p o s e s o l u t i o n a l g o r i t h m s a n d p r e s e n t p r e l i m i n a r y c o m p u t a t i o n a l re s ul ts .
Fir s t Mode l
2 . 1 F o r m u l a t i o n
I n t h i s m o d e l , a s s u m i n g t h a t a s e p a r a t i n g h y p e r p l a n e H e x i s t s , w e s t r i v e t o
m a x i m i z e t h e m i n i m u m d i s t an ce o f an y g i v en p o i n t t o H = {z lp tz a = O, z ~ R }.
I f n o s u c h h y p e r p l a n e e x i st s, w e l o o k f o r a h y p e r p l a n e H s u c h t h a t t h e m a x i m u m
d i s t a n c e o f a n y m i s c la s si fi e d p o i n t t o t h e h y p e r p l a n e H b e m i n i m i z e d . I n b o t h
c a se s, th e h y p e r p l a n e H is d e t e r m i n e d b y s o lv i n g t h e m a t h e m a t i c a l p r o g r a m m i n gpro b le m (see Ca val i e r e t a l . I-3] ).
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Novel Approaches to the Discr iminat ion Problem 519
m a x w
s. t . p x i + a > w i e I = {1 . . . , r} (1 )
p y J + a < - w j e J = {1 . . . . , s }
Ilpl122 = 1
w h e r e t h e n o n l i n e a r c o n s t r a i n t IlP ll2 = 1 e n s u r e s t h a t p t x ~ + a a n d p ty j a
r e p r e s e n t t h e e u c l id i a n d i s t an c e f r o m p o i n t s x ~ a n d y J t o t h e h y p e r p l a n e H =
{ p z + a = 0 } . I g n o r i n g t h is c o n s t r a i n t i s t e m p t i n g s i n ce th e r e s u l t i n g r e l a x e dp r o g r a m i s l in e a r ( s ee F r e e d a n d G l o v e r 1 -5 ] 1 6 ], G l o r f e l d a n d G a i t h e r [ 9 ]) .
H o w e v e r it l e a d s t o in c o n s i s t e n c i e s t h a t c a n n o t b e s a t i s fa c t o r i ly r e s o l v e d , i n s p i t e
o f n u m e r o u s a t t e m p t s ( s e e K o e h l e r [ 1 6 ] , R u b i n 1 -2 1] a n d M a r k o w s k i a n d
M a r k o w s k i 1 -20]). A r e c e n t p a p e r a l o n g t h i s li n e, w h i c h r e m o v e s s o m e o f t h e
d i ff ic u lt ie s a s s o c i a t e d w i t h t h e l i n e a r p r o g r a m m i n g f o r m u l a t i o n , i s t h a t o f G l o v e r
[ 1 0 ] w h e r e t h e n o r m a l i z i n g c o n s t r a i n t
- s ~ , p x i + r ~ p y J = 1i ~ l j ~
is su b s t i t u t e d t o t h e r e v e r s e c o n v e x c o n s t r a i n t
Iip21122 ~ 1 .
I f a s e p a r a t i n g h y p e r p l a n e e x i s ts , w i s n o n n e g a t i v e a t t h e o p t i m u m , a n d ( 1) is
e q u i v a le n t t o th e re l a x e d c o n v e x p r o g r a m m i n g p r o b l e m
m a x wp a w
s . t . p~x ~ + a > w
p t y j + a < - - w
Ilp[122 < 1
i e l
j e J
(2 )
w h e r e t h e n o n l i n e a r c o n s t r a i n t i s o b v i o u s l y t ig h t a t th e o p t i m u m . W e r e fe r t o
t h i s c a s e a s t h e c o n v e x c a se . I f n o s e p a r a t i n g h y p e r p l a n e e x is ts , i.e . t h a t t h e
i n t e r s e c t i o n o f t h e c o n v e x h u l l s o f X a n d Y h a s a n o n e m p t y i n t e r i o r , t h e n ( 1 ) is
e q u i v a l e n t t o t h e r e v e rs e c o n v e x p r o g r a m :
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520
m a x wp a~w
s. t . p t x i + a > w
p t y j + a < - - w
IlPll 2 _ 1
i e I
j ~ J
P. Marco t te and G . Savard
(3)
o r , a f t e r h a v i n g p e r f o r m e d a n o b v i o u s c h a n g e o f v a r ia b l e :
m i n wp,a,w
s. t . p x i + a > - w i ~ I (4 )
p t y J + a < w j ~ J
I l p l l ~ > 1
w h o s e o p t i m u m w i s s t r i c t l y p o s i t i v e . T h i s l a t te r p r o g r a m b e i n g r e v e r s e c o n v e x
w e w i l l r e fe r t o t h e n o n s e p a r a b l e s i t u a t i o n a s th e r e v e r se c o n v e x c a s e .
W e w i l l a l s o r e f e r t o t h e s t r i c t l y c o n v e x c a s e i n t h e c a s e w h e r e t h e r e e x i s t s a
s t r ic t s e p a r a t i o n h y p e r p l a n e p t z + a - - 0 , i .e . t h a t w i s s t r i c t l y p o s i t i v e i n (2 ). T h e
l i n e a r c a s e w i ll c o r r e s p o n d t o t h a t s i t u a t i o n w h e r e t h e s e t s X a n d Y c a n b e
s e p a r a t e d , b u t n o t s t r ic t l y , i.e . t h a t t h e o p t i m a l v a l u e o f w i n ( 2) i s z e r o . U n d e r
o u r t e r m i n o l o g y , t h e r e i s n o s t r ic t l y r e v e r s e c o n v e x c a se .
2 .2 E q u i v a l e n t F o r m u l a t i o n
W e f ir st s h o w t h a t t h e f ir s t v e r s i o n o f t h e d i s c r i m i n a t i o n p r o b l e m D P 1 i s
e q u i v a l e n t t o s o m e d i s t a n c e p r o b l e m .
T h e o r e m 1 : T h e d i s c r i m i n a ti o n p r o b l e m D P 1 is e q u i v a l e n t t o th e m i n i m u m n o r m
p r o b l e m
m in I ]q l]2q b
s t q t x i b > 1 i ~ I
5 )
qt y J + b <_ - I j ~ J
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No vel Approaches to the Discrimination Problem
i n t h e s t r i c t l y c o n v e x c a se , t o t he m a x i m u m n o r m p r o b l e m
m a x Ilqll22q b
s . t . q t x i + b > - 1 i ~ l
q~yJ + b < l j e J
i n t h e r e v er s e c o n v e x c a se , a n d t o th e m a x i m u m n o r m p r o b l e m
m ax I lq ll2q b
s t qtxi 4- b >_ i ~ I
q t yJ + b _ < O j e J
- l _ < q k _ < l k = l . . . . . n
i n t h e l i n e a r c a s e .
521
(6)
( 7 )
Proof.
(a) S t r i c t l y c o n v e x c a s e . F i r s t n o t i c e t h a t a n y o p t i m a l s o l u t i o n t o (2 ) m u s t s a t is f y
p 0 . O t h e r w i s e w e w o u l d h a v e a > w a n d a _< - w , i.e . w = 0 , a n i m p o s s i b i l i t y
s i n c e w > 0 a t t h e o p t i m u m i n t h e s t r i c t ly c o n v e x c a s e . S i m i l a r l y , q 0 a t th e
o p t i m u m o f (5 ).
L e t ( p *, a * , w * ) b e a n o p t i m a l v e c t o r f o r (2 ). T h e n ( q* , b * ) = ( p * / w * , a * / w * ) is
w e l l d e f i n e d f o r ( 5 ) . A s s u m e i t i s n o t o p t i m a l f o r ( 5 ) , a n d l e t ( ~ , / ~ ) b e o p t i m a l
ins tea d . T h e n I1 11 < I Iq*l l a n d ( if , a , i f ) = ( / 1 1 ~ 1 1 , b / l l l l , 1 / 1 1 1 1 ) i s f e a s i b l e f o r ( 2 )
w i t h f f = 1 / 1 1 ~ t l > 1/llq*ll = w / l l p l l = w * ( t h e c o n s t r a i n t I I p l l < 1 i s t i g h t a t
t h e o p t i m u m ) , i n c o n t r a d i c t i o n w i t h t h e o p t i m a l i t y o f w * . H e n c e ( q* , b * ) i s
o p t i m a l f o r (5 ).
N o w l e t ( q *, b * ) b e o p t i m a l f o r (5 ) a n d d e f i n e (p * , a * , w * ) = ( q * / l l q * 1 1 , a / l l q I I ,1 /llq *ll). A g a i n , a s s u m e t h a t ( p * , a * , w * ) i s s u b o p t i m a l , l e t (/~ , a , f ) b e o p t i m a l
w i t h f > w * a n d d e f i n e ( iT , b ) = ( / ~ /f , a / f ) . W e h a v e : 1 1 4 1 1= I l P l l / f = l i f t <
I / w * = IIq * II, i n c o n t r a d i c t i o n w i t h t h e o p t i m a l i t y o f q * .
(b) R e v e r s e c o n v e x c a s e . F i r s t, n o t e t h a t , i n th e r e v e r s e c o n v e x c a s e , p r o b l e m (6 )
is b o u n d e d . O t h e r w i s e l e t (q(k), b(k)) b e a fe a si bl e, u n b o u n d e d s e q u e n ce . W e h a v e :
q k ) t b k ) - - 1
x i + >tl(q k), btkJ)l II(q k), btk))lr - - iI(qtk) , btk~)l
L e t (q *, b * ) b e a n y c o n v e r g e n t s u b s e q u e n c e o f t h e b o u n d e d s e q u e n c e
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522
(q(k)/ll(q (k), b(k))ll, b(k)/ll(qtk) b(k))ll) .
W e t h e n h a v e , b y c o n t in u i t y ,
q t x i + b * > 0
P. M arcotte and G. S avard
an d , s i mi l a rl y :
q , t y j + b * <_ 0
an d (q * , b * ) d e t e rmi n es a (n o t n eces s a r i l y s t r i c t ) s ep a ra t i o n h y p e rp l an e , an i m-
p o s s i b i l i t y s i n ce w e a r e i n t h e r ev e r s e co n v ex ca s e . N o w , u s i n g t h e o n e - t o -o n e
re l a t i o n s h i p b e t w een f ea s ib l e s o l u t i o n s t o (3) (w i t h w > 0 ) an d f ea s i b le s o l u t i o n s
t o 6 ) :
(q, b) = ( p / w , a / w ) ,
t h e p r o o f i s s i m i la r t o t h e p r e v i o u s o n e , m o d u l o s i gn r e ve r sa l.(c) L i n e a r c a s e . A ny feas ib le so lu t ion to (7) wi l l p ro v ide a feas ib le so lu t io n , i .e . a
s o l u t i o n w i t h a n o n z e r o v e c t o r p . [ ]
R e m a r k : In t h e s t r i c t l y co n v ex ca s e , t h e d i s c r i m i n a t i o n p ro b l em i s eq u i v a l en t t o
p r o j e c ti n g t h e o r i g i n o n t h e c lo s e d , c o n v e x p o l y h e d r o n
{ q e R n l q t x + b > l V i e I
q t y J + b < - i V j ~ J
fo r s o m e b ~ R} .
T h i s p o l y h e d ro n d o es n o t co n t a i n t h e o r i g i n (s ee f ig u re 1 ).
I n t h e r ev e r s e co n v ex ca se , i t r ed u ces t o f i n d i n g t h e ( ex tr eme) p o i n t o f m ax i m u m
e u c l id i a n n o r m o f th e c lo s ed c o n v e x p o l y h e d r o n
{ q E R n [ q t x i + b > - 1 V i ~
q ty J + b < l V j ~ J
fo r s o m e b ~ R}
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P 2
N o v e l A p p r o a c h e s t o t h e D i s c r i m i n a t i o n P r o b l e m 5 23
O
F i g 1 : T h e c o n v e x c a s e
I J
P l
h a v i n g t h e o r i g i n a s a n i n t e r i o r p o i n t ( se e f i g u r e 2 ). I n t h e l i n e a r c a s e , p r o b l e m
(5 ) is in f e a si b le , w h i le p r o b l e m (6 ) is u n b o u n d e d .I t is a l s o p o s s i b l e to r e f o r m u l a t e t h e d i s c r i m i n a t i o n p r o b l e m , i n t h e r e v e r s e
c o n v e x c a s e , a s a b i l ev e l p r o g r a m m i n g p r o b l e m .
Theorem 2: I n t h e r e v e r s e c o n v e x c a s e , (3 ) a n d (6 ) a r e e q u i v a l e n t t o t h e l i n e a r
b i l e v e l p r o g r a m :
~ 1 t . e 2 t u 2m a x c u +
p a
s.t . A p + ae I >_ - e 1
Bp + ae 2 <_ e 2
( u l , u z ) 6 a r g m a x -e l~ u 1 e2 u 2 (8)
s . t . - A t u 1 + B~u 2 = p
e l t u I J e 2 t u 2 = 0
u 1, u 2 >_ 0
w h e r e A = ( x 1 . . . , x ) t, B = ( y l . . . . . y~)r, e 1 = ( 1 . . . . . 1 )r e R r a n d e 2 =
1 . . . . . 1 ) t ~ R s .
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P2
F i g 2 : T h e r e v e r se c o n v e x c a s e
5 2 4 P M a r c o t t e a n d G S a v a r d
Pl
Proof The transformation of a concave quadrat ic program into a linear bilevel
program has been shown to be valid in Konno [181 using linear dualityarguments. []
2.3 Com plexity Ana lysis
Theorem 3: The discrimination problem DP1 is in P in the convex (strictly convex
9 r linear) case and strongly NP-complete in the reverse convex case.
Proof (a) In the strictly convex case, the result follows from the existence of
polynomial algorithms for the monotone linear complementari ty problem which
constitutes an extension of the convex quadratic programming problem (see
Kojima et al. [14]).
(b) In the linear case, there must exist a nonzero vector p and a scalar a such
that the set of linear inequalities
p t x i + a > _ O i ~ I
p t y ~ + a < 0 j ~ J
is satisfied. One way to enforce the condition p ~ 0 is simply to impose the
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Novel Approaches to the DiscriminationProblem 525
a d d i t i o n a l c o n d i t i o n Pk > 1 or Pk < -- 1) f o r s o m e i n d e x k . S in c e it is u n k n o w n
a priori w h i c h i n d e x k w i ll c o r r e s p o n d t o a n o n z e r o c o e t ti e ie n t P k, o n e h a s t o
s o lv e , in t h e w o r s t c a s e , t h e 2 n l i n ea r f ea s i b i l it y p ro b l em s :
p t x i + a > _ O i ~ I
pty~ + a < 0 j ~ J 9a)
pk > 1
a n d
p t x i + a > O i e I
pty~ + a < 0 j e J 9b)
Pk <-~ - -1
f o r k = 1 . . . , n , a n d p o l y n o m i a l i t y i s a c o n s e q u e n c e o f t h e p o l y n o m i a l i t y o f l i n e a rp r o g r a m m i n g see K h a c h y a n [1 5 ]) .
c ) I n t h e r e v e rs e c o n v e x ca s e, th e s t r o n g N P - c o m p l e t e n e s s o f D P 1 f o l lo w s
f r om t h e s tr o n g N P - c o m p l e t e n e s s o f t h e m a x i m u m n o r m p r o b le m se e F r e u n d
a n d O d i n [ 7 ] o r B o d l a e n d e r e t a l. [ 2 ]) . [ ]
Coro l lary: T h e e x i s te n c e o r n o n - e x i s t e n c e o f a d i s c r i m i n a t i n g h y p e r p l a n e c a n b e
d e t e r m i n e d i n p o l y n o m i a l ti m e .
Proof. F ro m t h eo r em 3 , p a r t b ), t h e r e fo l lo w s t h a t t h e exi s ten ce o f a d i s c r i mi n a t i n g
h y p e r p l a n e c a n b e d e t e r m i n e d b y s o l v in g fo r t h e e x i s te n c e o f a f e as ib l e s o l u t i o n
t o o n e o f 2 n l i n ea r s y s t ems . H en c e t h e r e s u lt . [ ]
2 .4 S o lu t i o n A lg o r i t h m s a n d N u m er i ca l R es u l t s
So l u t i o n a l g o r i t h ms a r e b a s ed o n t h eo rem 1, w h i ch s t a t e s t h e eq u i v a l en ce b e t w een
D P 1 a n d q u a d r a t i c p r o g r a m m i n g . I n t h e c o n v e x c a se i t i s e a s il y s o l v e d a s a
p r o j e c t i o n p r o b l e m f o r w h i c h e ff ic ie n t a l g o r i t h m s e x is t se e W o l f e [ 23 ] o r t h e
s u r v e y b y L i n a n d P a n g [ 1 9 ]) . I n t h e r e v e r se c o n v e x ca s e, w e s o l v e d D P 1 u s i n g
a c o d e i n i ti a ll y d e s i g n e d f o r so l v i n g l i n e a r bi le v e l p r o g r a m m i n g p r o b l e m s se e
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526
Table 1: Possible param eters combinations
P. M arcotte and G . Savard
#x 0.0 0.0 0.0 0.0 0.0 0 .0
Dispersion # r 0.5 1.0 2.0 4.0 8.0 i6.0parameters Ex I I I I I IZr I I 41 41 161 161
Sam plesize (r,s) (20,10) (20,15) (20,20) (30,15) (30,22) (30,30) (40,20) (40,30) (40,40)
Dimension n 2 3 4
H a n s e n e t a l [ 11 ]) . T h i s a l g o r i t h m i m p l e m e n t s i d e as o f l o gi c p r o g r a m m i n g w i t h i n
a B r a n c h - a n d - B o u n d s c h em e a n d c o n v e rg e s t o a g l o b l o p t i m u m i n f in i te l y m a n y
s te p s. N e c e s s a r y o p t i m a l i t y c o n d i t i o n s e x p r e s s e d i n t e r m s o f t i g h t n e s s o f t h e
s e c o n d l e v e l ' s c o n s t r a i n t s a r e u s e d f o r f a t h o m i n g o r s i m p l i f y i n g s u b p r o b l e m s
t h r o u g h e l i m i n a t i o n o f v a r i a b l e s, b r a n c h i n g , a n d o b t a i n i n g p e n a l t i e s si m i l a r to
t h o s e u s e d i n m i x e d i n t e g e r p r o g r a m m i n g . F o r t h o s e p r e l i m i n a r y r e s u l t s , n o
a t t e m p t s h a v e b e e n m a d e a t s p e c ia l iz i ng th i s a l g o r i t h m t o t h e p a r t i c u l a r s t r u c t u r e
o f 8 ) .O u r e x p e r i m e n t a l d e s i gn f o l lo w s c lo s e ly t h a t o f B a jg i er a n d H i l l [ 1 ]. T h e
d i s c r i m i n a t i n g p o i n t s a r e d r a w n f r o m m u l t i v a r i a t e n o r m a l p o p u l a t i o n s w i t h
v a r i a b l e d i s p e r s i o n p a ram e t e r s (# x , / ~ r , 2 7x , 2 7 r ), s am p l e s i ze s r , s an d s p ace
d i m e n s i o n n . T a b l e 1 s h o w s t h e c o m b i n a t i o n s u s e d f o r t h e a c t u a l e x p e r i m e n t s .
F o r e a c h o n e o f t h e 6 x 9 x 3 = 1 62 c o m b i n a t i o n s t h a t h a v e b e e n t e s t e d , a s e t
o f 1 0 r a n d o m p r o b l e m s h a s b e e n g e n e r a t e d . N u m e r i c a l r e s u lt s a r e p r e s e n t e d i n
t a bl e s 2, 3 a n d 4 , w h e r e m r e f er s t o t h e a v e r a g e ( C P U - t i m e a n d n u m b e r o f n o d e s
e x p l o r e d i n th e b r a n c h - a n d - b o u n d s c h em e ) o f t h e c o r r e s p o n d i n g s e t o f p r o b l e m s ,
s , , t o t h e s t a n d a r d d e v i a t i o n a n d m e t o t h e m e d i a n o f t h e o b s e r v a t io n s , T h e
b il ev e l p r o g r a m m i n g c o d e, w r i tt e n in F o r t r a n , h a s b e e n r u n o n a S U N S P A R K
w o r k s t a t i o n .
A s e x p e c t e d , th e p r o b l e m ' s d i f f ic u l ty i s c l o s e ly r e l a t e d t o t h e n u m b e r o f n o d e s
e x p l o r e d in t h e b r a n c h - a n d - b o u n d s c h em e u n d e r l y i n g t he b i le v el p r o g r a m m i n g
a l g o r i th m , a n d i n c re a s e s w i t h t h e d e g r e e o f o v e r l a p b e t w e e n t h e t w o s et s o f p o i n t s
X a n d Y. W h e n t h e o v e r l a p i s w e a k , t h e n t h e n u m b e r o f n o d e s t o b e e x p l o r e d in
o r d e r t o o b t a i n a n o p t i m a l s o l u t i o n is a l m o s t i n s e ns it iv e t o t h e s p a c e d i m e n s i o n
n. T h i s h o w e v e r is n o t t h e c a s e w h e n t h e o v e r l a p i s s t r o n g , i.e . w h e n t h e m e a n s
# x an d # r a r e c l o s e . F o r i n s t an ce , w i t h t h e d a t a s e ts (# x , # r , 2 7x , Z ' r ) = (0, .5 .; I , I )
a n d ( # x , # r , S x , 2 ; r ) = (0 , 1, I , I ) t h e n u m b e r o f n o d e s e x p l o r e d i s a p p r o x i m a t e l y
t h e s a m e i n d i m e n s i o n 2 ( n = 2 ) w h i l e i t i s i n th e r a t i o 2 to 1 w h e n t h e d i m e n s i o n
i s i n c r e a s e d f r o m n = 2 t o n = 4 . W e a l s o n o t e d t h a t t h e m o s t d i ff ic u l t p r o b l e m s
u s u a l ly c o r r e s p o n d e d t o t h e s i t u a t io n w h e r e t h e n u m b e r o f p o i n t s i n e a c h s a m p l e
we re c l o s e t o eac h o t h e r ( r ~ s ). Fo r t h e ea s i e r p ro b l em s ( r << s o r s << r ) t h e
m e d i a n w a s c l o s e t o t h e a v e r a g e a n d t h e s t a n d a r d d e v i a t i o n w a s s m a ll , a n
u n u s u a l f e a t u r e i n t h e s o lu t i o n o f p r o g r a m s v i a b r a n c h - a n d - b o u n d m e t h o d s .
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53
3 S e c o n d M o d e l
P. M arcotte and G. S avard
3 . 1 F o r m u l a t i o n s
M i n i m i z i n g t h e n u m b e r o f m i c la s si fi e d p o i n t s r e s ul ts i n t h e m i x e d i n t e g e r p r o -
g r a m m i n g p ro b l e m D P 2 :
m i n n x + n rp a
w h e r e n x = c a r d { x ~ l p t x ~ + a < 0 } an d n r = c a r d { y J [ p t y j + a > 0 } . I n t r o d u c i n g
b i n a ry v a r iab l e s ~ (~ = 0 i f x i i s no t m isc lassi f i ed , 1 o therw ise) an d t/ j (qj = 0 i f
y J is n o t mi s c l a s si f ied , 1 o t h e rw i se ) , an d o b s e rv i n g t h a t w e m u s t i m p o s e in s o m e
w a y th e c o n s t r a i n t p 0 , w e o b t a i n t h a t D P 2 c a n be s o lv e d b y s o l v in g t h e t w o
m i x e d i n t eg e r p r o g r a m s
m i n ~ ~ + ~ t / jp a ~ ~l i~ l jE J
s.t. M ~ i >_ - p t x i + a ) i ~ I
M t l j >_ p t y j + a J ~ J ( l l a )
~ j e { o 1}
- - l < p k < _ l k = l . . . . , n
P l = - 3
a n d
m i n 2 ~ , + 2 r tJp a ~ ~l i~ l j~ J
s.t. M~i >_ - - p tx i + a) i e I
M t l j > p t y ~ + a J ~ J (1 lb)
~i, ~/j ~ {0, 1}
- - l < _ p k < _ l k - - 1 . . . . . n
P i = 6
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N o v e l A p p r o a c h e s t o t h e D i s c r i m i n a t i o n P r o b l e m 5 3
w h e r e M is a p o s i t iv e c o n s t a n t s u f f ic i e nt ly l a r g e t o e n s u r e t h a t p r o b l e m s l l a )
a n d 1 l b ) a r e f e a s ib l e f o r a ll a d m i s s i b le v a l u e s o f p a n d a a n d 6 i s a s m a l l p o s it i v e
c o n s t a n t . W e h a v e t h e f o ll o w i n g t h e o r e t i c a l r e s u lt :
T h e o r e m 4 : F o r D P 2 t o b e e q u i v a l e n t t o l l a ) a n d l l b ) i t is s u ff ic i en t t h a t th e
c o n d i t i o n
M > 2 t m a x ~ xgl m a x ~ tY ~ t}i~l k = l j ~ J k = l
b e s a t i s f ie d .
Proof . I f a < - m a x / ~ k I x~ l < ~ k p k X ~ f o r a l l p o i n t s x ' i n x , r e c al l t h a t [PRI < 1)
t h e n a l l p o i n t s i n X a r e m i s c la s s i fi e d . O n t h e o t h e r h a n d , i f a > m a x ~ ~ k l x ~ l , t h e n
a l l p o i n t s i n X a r e w e l l c l a s si f ie d . A s i m i l a r r e s u l t h o l d s f o r p o i n t s i n Y , r e p l a c i n g
x i b y y J i n th e a b o v e i n e q u a li ti e s . W e c a n t h e r e f o r e c o n c l u d e t h a t , w i t h o u t l o s s
o f g e n er al it y , la l c a n b e b o u n d e d b y m a x , ~ , ~ = l l x ~ l + m a x i ~ s ~ = x l Y ~ l :
C o n s e q u e n t l y , I p t x i + a l a n d I p ' y j + a l w i l l a l w a y s a s s u m e v a l u e s l e s s t h a n2 { m a x , ~ , ~ = ~ Ix~ l + m a x j ~ s ~ = ~ lY/~I}, a s c l ai m e d . [ ]
O n e c a n s u b s t i t u te t o th e m i x e d i n te g e r p r o g r a m s 1 l a ) a n d l l b ) t h e s in g le
b i le v e l p r o g r a m :
m i n ~ , + ~ q j + L [ ~ i + X [ 3 i + 7 1p,a,~,~,lt i~l j~ J L eI je J
s.t. M ~ i > - - ( p t x i + a )
M r l j > p t y j + a
2/~ + p l = 3
- - l < p k < l
i ~ I
j ~ J
k = 1 , . . . , n
~ , f l , ? ) ~ a r g m a x ~ o q + ~ f l j +
i ~ l j ~ J
s.t. ~i -< r ~i < 1 - ~i
r > 0 i ~ I ,
,8j <_ rlj ,Sj <_ l - rli
1 2 )
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532 P. M arcotte and G. Savard
t l j > O j e J
? _ < p ? < 1 - / ~
? _ > 0
w h e re L i s a s u i t ab l y l a rg e co n s t an t . T h e c o n s t r a i n t s e t o f th e l o w e r lev e l f o r ce s
v a r ia b l e s ~ , f lj a n d ? t o t a k e n o n z e r o v a l u e s w h e n e v e r a b i n a r y v a r i a b l e ~ , r/i
o r is n o t e q u a l to z e r o o r o n e . I n o r d e r t o m i n i m i z e t h e s u m o f t h e ~ ' s , fi rs
an d ? , t h e u p p e r l ev el w i ll s et t h e co n t i n u o u s v a r i ab l e s (~ i's , ~ / fs an d / ~ ) , t o e i t h e r
0 o r 1. I n d e e d , t h e l o w e r l e v el s i m p l y t r a n s la t e s i n t o a n o p t i m i z a t i o n f o r m t h e
re l a t i o n s h i p s
~i = m in{ ~i, 1 - ~i}
fli = min{ ~/j, 1 - ~/j}
? = m i n { , 1 - / ~ } .
T h e l o w e r le v el p r o g r a m , t o g e t h e r w i t h t h e u p p e r l ev e l c o n s t r a i n t
2/~ + p l = 1
e n s u r e s t h a t P l w i ll t a k e e it h e r v a l u e - 1 o r 1, t h u s a v o i d i n g t h e d e g e n e r a t e
s o l u ti o n . T h e s o l u t i o n t o D P 2 w i ll n o t i n g e n e r a l be u n i q u e , a n d s o l u t i o n m e t h o d s
b a s e d o n l i n e a r p r o g r a m m i n g r e l a x a t i o n ( b r a n c h - a n d - b o u n d , c u t t i n g p l a n e s ,
L ag ran g ean r e l ax a t i o n ) w i l l f av o r ex t r ema l s o l u t i o n s i . e . , i n t h i s co n t ex t ,
h y p e r p l a n es g o i n g t h r o u g h a t l e a s t n p o i n t s o f e i t h e r X o r Y (s ee f i g u re 3 fo r a
t w o - d i m e n s i o n a l e xa m p l e ). I n t h i s c a s e it is n a t u r a l t o s e e k, a m o n g t h e s e t o f
h y p e r p l a n e s m i n i m i z i n g t h e n u m b e r o f m i s c la s si fi e d p o i n ts , a n h y p e r p l a n e t h a t
mi n i m i zes a s w e l l t h e s e t o f w e ll -c l a ss if i ed p o i n t s . T h u s w e o b t a i n t h e m e t a -b i l ev e l
f o r m u l a t i o n :
m a x m i n ( m in f x i a,p a Ix i r welliX)
s .t . (p , a) ~ ar g m in n x + nr
m i n _ p t y J _ a }yJ r well Y)
1 3 )
IlPll2 ~ 1
w h e re w e l l (X ) an d w e l l(Y ) d e n o t e t h e s e ts o f w e l l -c l a ss i fi ed p o i n t s i n X an d Y
respec t ive ly , whi l e n x ( r e s p ect i v e ly n y ) d en o t e s t h e n u m b e r o f mi s c l a s s if i ed p o i n t s
in X (resp ect ively in Y).
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Novel Approaches to the DiscriminationProblem 533
P~ 0
..o%o0 0 O
9 ~ a = O
m
P l
Fig. 3: An exterm al solution
In v i ew o f t h e d i f f i cu lt y o f s o l v i n g (1 3 ) , w e w i ll in s t ead co n s i d e r a g o a l p ro -
g r a m m i n g f o r m u l a t i o n w i t h p r i m a r y o b je c ti ve t h e n u m b e r o f m i sc l as s if ic a ti o nsan d s eco n d a ry o b j ec t iv e t h e s ep a ra t i o n o f t h e se t s o f w e l l -c l a ss if i ed p o i n t s . T h i s
r e s u l t s in t h e fo l l o w i n g p ro ced u re :
G o a l P r o g r a m m i n g A l g o ri th m
1. L et (p*, a* ) e ar g m inp, a n x + n r a n d I x ( r e s p ec ti v e l y Iv ) d en o t e t h e i n d ex s e t
o f wel l -c lass i f ied po in t in X ( respec t ive ly Y).
2 . So l v e t h e p ro j ec t i o n p ro b l em :
min t lql l2q b
s.t. q tx l + b >_ 1 i E I x
q t y J + b < - I j e l r 9
(14)
I f (14) i s feas ib le ( s t r i c tly con vex case) l e t (q* , b*) be i t s so lu t io n an d se t: p* =
q* /tlq * II 2, a * = a*/llq*}l 2.3 . O u tp u t (p* , a* ) . [ ]
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534
3 .2 Com plex i ty Ana l ys i s
P. M arcotte and G . Savard
I n t h e c o n v e x c a se , t h e o p t i m u m o f (14) is z e r o , a n d o u r g o a l p r o g r a m m i n g
f o r m u l a t i o n r e d u c e s D P 2 t o D P 1 . I n t h e r e v e r s e c o n v e x ( o r i n t h e g e ne r a l) ca s e,
w e o b t a i n t h e f o l l o w i n g w o r s t - c a s e r e s u lt :
T heorem 4 : T h e d e c i s i o n p r o b l e m c o r r e s p o n d i n g t o D P 2 i s s t r o n g l y N P -
c o m p l e t e .
Proof T h e d e c i s io n p r o b l e m c o r r e s p o n d i n g t o D P 2 c a n b e s t a te d a s:
D o e s t h e r e e x is t a h y p e r p l a n e H s u c h t h a t t h e n u m b e r o f m i s c l a s si f ic a t io n s
i s l es s o r e q u a l t o K ?
(a ) D P 2 i s i n N P .
L e t I d e n o t e t h e c a r d i n a l i t y o f a m a x i m a l s e t S o f a f f in e l y i n d e p e n d e n t p o i n t s i n
X w Y an d l e t n ' = ca rd (S ) = r a in { l , n }. In p rac t i ce we wi l l u s u a l l y h av e t h a t r + s
i s m u c h l a r g e r t h a n n a n d w e e x p e c t n ' = n . T h e r e a l w a y s e x i s ts a s o l u t i o n ( p, a )t o D P 2 s u c h t h a t t h e n ' p o in t s i n S li e o n t h e h y p e r p l a n e ptz + a = 0 . T h e re fo r e
a s o l u t i o n t o D P 2 c a n b e c h a r a c t e r i z e d b y s p e c i f y in g t h e f i n it e s e t S . F o r a g i v e n
S , t h e v a r i a b l e s p a n d a a r e d e t e r m i n e d a s s o l u t i o n s o f t h e ( p o s s ib l y u n d e r -
d e t e r m i n e d i f n ' < n ) l i n e a r s y s t e m
tz + a = 0 fo r al l z e S ,
a n d , p r o v i d e d t h a t t h e i n p u t p o i n t s x ~ n d y J a r e r a t i o n a l , p a n d a a r e a l so r a t i o n a lw i t h l e n g t h s p o l y n o m i a l l y b o u n d e d i n t h e l e n g t h o f t h e i n p u t . F o r g i v e n ( p, a ),
c h e c k i n g t h a t t h e n u m b e r o f m i s c l a s s if i c a ti o n s d o e s n o t e x c e e d K c a n b e p e r -
f o r m e d i n t i m e p r o p o r t i o n a l t o t h e l e n g t h o f (p , a ), th e l e n g t h o f t h e i n p u t a n d
t h e n u m b e r r + s o f p o i n t s i n X u Y, i.e . i n p o l y n o m i a l ti m e w i t h r e s p e c t t o th e
i n p u t s iz e, t h e n u m b e r o f b i ts r e q u i r e d t o e n c o d e t h e d a t a x i, i ~ I a n d yJ, j ~ J .
( b) D P 2 i s N P - c o m p l e t e .
T h i s r e s u l t w il l b e o b t a i n e d b y p o l y n o m i a l ( a c t u a l ly li n e a r ) r e d u c t i o n o f t h e c l o s e d
d e n s es t h em i s p h e r e p r o b l e m ( C D H ) , w h o s e N P - c o m p l e t e n e s s h a s b e e n p r o v e d
b y J o h n s o n a n d P r e p a r a t a [ 1 3 ] , t o D P 2 . T h e c l o s ed d e n s e s t h e m i s p h e r e p r o b l e m ,i n it s sa t is f ia b i li ty f o r m , c a n b e s t a t e d a s ( se e G a r e y a n d J o h n s o n [ 8 ] ) :
G i v e n a s e t W o f m p o i n t s i n R , d o e s t h e r e e x i st a v e c t o r q i n R a n d a
s c a l a r b s u c h t h a t a t l e a s t L p o i n t s i n W l ie o n t h e s a m e s id e o f ( o r o n )
t h e h y p e r p l a n e H = {q ' z = 0}, i .e .: ca rd {w ~ W l q 'w > 0} > L?
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No vel Approaches to the Discrimination Problem 535
O
~ 0
Fig 4: Solving CD H
C o r r e s p o n d i n g t o C D H w e f o r m u l a t e a n i ns ta n c e o f D P 2 w i th X = W w T a n d
Y = T w h e re T co n t a i n s m - L + 1 co p i e s o f t h e o r i g in , an d we s e t K = m - L .
T h e n a n y s o l u t i o n t o t h i s D P 2 m u s t b e a h y p e r p l a n e g o i n g t h r o u g h t h e o r i g i n
a = 0 ) an d l eav e a t m o s t m - L p o in t s o f X m i s c l a s si f ied , i.e . t h a t a t l e a s t L p o i n t s
i n X e q u i v a l e n t l y L p o i n t s in W ) li e o n t h e s a m e s i d e o f H , t h u s s o l v i n g C D H
see f igure 4 ). [ ]
3 .3 S o l u t i o n A l g o r i t h m s
M i n i m i z i n g t h e n u m b e r o f m i s c la s s if i ed p o i n t s c a n b e a c h i e v e d b y s o l v in g t h e
b i le v e l p r o g r a m s 1 2). H o w e v e r , f o r n = 2 , a n O r + s ) 2 l g r + s ) ) a l g o r i t h m i s
a v a il a b le , b a s e d o n t h e f a ct t h a t t h e d i s c r im i n a t i n g h y p e r p l a n e h a s t o g o t h r o u g h
a t l e a s t t w o p o i n t s o f X w Y. I n i t s b as i c f o r m t h i s a l g o r i t h m c a n b e e x p r e s s e d a s
A l g o r i th m 2 - P o l
fo r a ll p o in t s z i n X w Y o
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536 P. M arcotte and G. Savard
0. S e t S = X u Y - { z } .
1. S e l e c t a n a r b i t r a r y a x i s g o i n g t h r o u g h t h e p o l e z.
2 . S o r t a l l p o i n t s i n S a c c o r d i n g t o t h e i r p o l a r a n g l e w i t h r e s p e c t t o t h e a x i s .
3 . S e l e c t a n a r b i t r a r y p o i n t z I i n S a n l e t H b e t h e h y p e r p l a n e s t r a i g h t l in e )
g o i n g t h r o u g h z a n d z 1.
4 . L e t N d e n o t e t h e n u m b e r o f m i s c l a s s i fi c a ti o n s w i t h r e s p e c t t o H .
5. le t S = S - {z 1 }.
i f S = ~ t h e n s t o p a n d o u t p u t N
ls s e t z I t o t h e p o i n t i n S c l o s e s t t o H a n d r e t u r n t o 4 .
I n a lg o r i th m 2 - P O L , s t e p 2 h a s c o m p l e x i t y O r + s) l g r + s )) . S ince , a f t e r s t e p
5 h a s b e e n p e r f o r m e d , t h e n u m b e r o f m i s c l a s s if i c a ti o n s c a n o n l y i n c r e a s e o r
d e c r e a s e b y 1 o r 2 , s t e p 4 c a n b e i m p l e m e n t e d i n c o n s t a n t t im e , a n d t h e o v e r a l l
w o r s t -c a s e c o m p l e x it y o f 2 - P O L is O r + s ) 2 l g r + s )) , a s p r e v i o u s l y c l a i m e d .
R e m a r k s : 1. I n t h e r e v e r se c o n v e x c a s e , 2 - P O L is a c o m p l e t e e n u m e r a t i o n s c h e m e .
I t is p o s s i b l e to i n c r e a s e i ts e ff ic i e nc y b y u s i n g s y m m e t r y r e l a t io n s h i p s a n d t h e
f a c t t h a t w e c a n r e st r ic t o u r s e a r c h t o h y p e r p l a n e s g o i n g t h r o u g h c o u p l e s x , y )
w i t h x ~ X a n d y ~ Y . A l s o , if p o i n t s u s e d a s p o l e s a r e s e l e c t e d in a s u i t a b l e o r d e r
c l o se n e i g h b o r s ) t h e n t h e s o r t in g s t e p 2 c a n b e i m p l e m e n t e d u s i n g r e o p t i m i z a t i o n
t e c h n i q u e s .
2 . A l g o r i t h m 2 - P O L c a n b e g e n e r al iz e d t o p r o b l e m s i n R n t o y ie ld a n
O r + s ) ~ l g r + s )) a l g o r i t h m , f o l l o w i n g t h e li n es d e v e l o p e d p r e v i o u s l y a n d t h e
r e c u rs iv e p r o c e d u r e m e n t i o n e d i n t h e p a p e r b y J o h n s o n a n d P r e p a r a t a 1 1 3] f o r
t h e d e n s e s t h e m i s p h e r e p r o b l e m . H o w e v e r s u c h a lg o r i th m s a r e n o t c o m p e t i ti v e
w i t h i m p l i c it e n u m e r a t i o n s c h e m e s i n h i g h d i m e n s i o n s , a s w e w i ll s ee .
3 .4 N u m e r i c a l R e s u l t s
W e c o m p a r e d t he ef fic ie nc y o f t h e b ile v el a p p r o a c h a n d t he 2 - P O L a n d N - P O L
e n u m e r a t i o n s c h e m e s fo r s o lv i n g D P 2 o n t h e se ts o f r a n d o m l y g e n e r a t e d p r o b -
l e m s p r e v i o u s l y d e s c r i b e d i n s e c t i o n 2 . 4 . A g a i n , n o a t t e m p t s h a v e b e e n m a d e t o
s p e c ia l iz e t h e B L P c o d e t o e x p l o it t h e s t r u c t u r e o f t h e b il e v e l p r o b l e m 1 2).
I n t a b l e s 5 , 6 a n d 7 w e p r e s e n t t h e n u m e r i c a l r e su l ts . N o t e t h a t , s in c e a l g o r i th m s
2 - P O L a n d N - P O L a re b a s e d o n e x p l i c i t i n c o n t r a s t w i t h implic i t ) e n u m e r a t i o n ,
s o l u t i o n t i m e s f o r t h o s e a l g o r i t h m s s h o u l d t h e o r e t i c a l l y b e e q u i v a l e n t f o r p r o b -
l e m s w i t h i d e n t i c a l r , s a n d n v a l u e s , a l b e i t d i ff e r e n t X a n d Y d a t a . T h e r e f o r e , f o r
g i v e n s a m p l e s iz e s, t h o s e 2 a l g o r i th m s w e r e n o t t e s t e d o n a l l t e n r a n d o m l y g e n e r -
a t e d s u b p r o b l e m s , a s i n g le o n e b e i n g s u ff ic ie n t t o s h o w t h e b e h a v i o r o f t h e m e t h o d s .
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N o v e l A p p r o a c h e s t o t h e D i s c r i m i n a ti o n P r o b l e m 5 7
Co n seq u en t ly , m ed ian an d s t an d a r d d ev ia t io n f ig u r es a r e n o t g iv en , b e in g eq u a l
to th e av e r ag e an d th e n u m b er ze r o r e sp ec tiv e ly .
I n v i ew o f t ab l e 5 , i t i s c l ea r t h a t 2 - P O L o u tp e r f o r m s th e b i l eve l ap p r o ac h f o r
so lv in g d i sc r im in a t io n p r o b le m s o n th e p l an e (n = 2). I n d eed , w h a tev e r t h e
d eg r ee o f o v e r l ap b e tw een X an d Y, p r o b lem s in v o lv in g h u n d r ed s o f p o in t s i n
each g roup cou ld be so lved wi thou t d i f f icu l ty . Never the less th is approach fa i l s
in d im en s io n s h ig h e r t h an 3 . I n d im en s io n 4 i t i s o u tp e r f o r m ed b y th e b i l ev e l
a lg o r i th m o n a ll t e st p r o b lem s , w i th th e ex cep t io n o f t h o se p r o b lem s co r r e -
spo ndin g to the f i r s t se t o f d ispers ion coef ficien ts . In d im ensions h igher th an 4 ,
a l g o ri th m N - P O L b e c o m e s i n tr a ct a b le . A r o u g h c a l c u l a ti o n s h o w s t h a t s o m e
2 x l0 s seco n d s w o u ld b e r eq u i r ed f o r so lv in g a D P 2 o f size 4 0 x 4 0 an d
d im en s io n 5 . Fo r so lv in g a D P 2 in v o lv in g th e sam e n u m b er o f p o in t s , 2 x 1 0 x3
s e c o n d s o f C P U t im e w o u l d b e r e q u ir e d i n d i m e n s i o n 1 0.
I n th e b i lev e l ap p r o ach , t h e p r o b lem s d i ff icu l ty i s d i r ec t ly p r o p o r t io n a l t o t h e
n u m b er o f n o d es ex p lo r ed in t h e b r an ch - an d - b o u n d t ree an d , a s i n d ica t ed in
sec t io n 2 .4 , i t i s r e l a t ed to t h e d eg r ee o f o v e r l ap b e twe en th e two g r o u p s o f p o in ts .
F o r p r o b lem s in v o lv in g a l a rg e n u m b er o f m i sc la s s if ied p o in t s , t h e av e r ag e
n u m b e r o f b r a n c h - a n d - b o u n d n o d e s c a n v a r y b y a f a c to r la r ge r t h a n 1 00 0 f o r
p r o b lem s o f s im i la r d im en s io n s g en e r a t ed th r o u g h d i ff e ren t m ea n s an d v a r i an ce-
cov ar ianc e m at r ices . F or the se t o f p rob lem s hav ing d ime nsions (40 , 20 , 4 ) ( see
tab le 7 ) th is fac to r go t as la rge as 1157 , whi le i t was a lways lower than 23 fo r
D P1 . Th i s can b e ex p la in ed b y th e f ac t th a t t h e n u m b er o f m i sc la s s if ica t io n s is
a f fec ted , t o a g r ea t e r ex t en t t h a t t h e o p t im a l v a lu e o f DP1 , b y th e d eg r ee o f
o v e r l ap b e tw een X an d Y. I n co n t r a s t t h e o b jec t iv e D P 2 is v e r y m u ch d ep en d en t
o n th e d eg r ee o f d i sp e r s io n o f t h e sam p le p o in t s.
These p re l imina ry resu l t s a re encourag ing , espec ia l ly in v iew of those resu l t s
o n DP 2 o b ta in ed o n m a in f r am e co m p u te r s f o r p r o b lem s o f s ize r = s = 5 0, n = 3
a n d r e p o r t e d i n t h e p a p e r s b y K o e h l e r a n d E r e n g u c [ 1 7 ] a n d S t a r e a n d
Jo ach im s th a le r [ 2 2 ] .
Conc lus ion
I n th i s p a p e r we in v es tig a ted , t h eo r e t i ca lly an d n u m er i ca lly , tw o f o r m s o f a
n o n p a r am e t r i c d i sc r im in a t io n p r o b lem , f o r wh ich n ew, a l t e r n a tiv e f o r m u la t io n s
wer e g iv en , an d sev e r a l a lg o r i th m s p r o p o sed . P r e l im in a r y r e su l t s o n sm a l l t o
m ed iu m - s i ze p r o b lem s a r e en co u r ag in g an d we in ten d , a s a seq u e l t o t h is w o r k ,
to t a i lo r so m e o f t h e m o r e p r o m is in g a lg o r i th m s to th e p a r t i cu la r s t r u c tu r e o f
th e d i sc r im in a t io n p r o b lem . I n p a r t i cu l a r we b e l i eve th a t t h e in c lu s io n o f n ew
o p t im a l i ty te s t s an d b o u n d s in t h e b il ev el p r o g r am m in g p r o ce d u r e th a t ex p lo i t
t h e s t r u c tu r e o f D P 2 co u ld s ign i fi can t ly d ec r ease co m p u t in g t im es .
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Table D
P2
d
a
s
oo
r
=
2
s=
1
r
=
2
s=
1
r
=
2
s
=
2
r
=
3
s=1
~x
:Cx
~r n
0
0
0
5I I 2
0
01
0 I I 2
0
0
2
0I 4 2
0
0
4
0I 4 2
0
0
8
0I
12
0
0
1
0I
12
n
c
n
c
n
c
n
c
n
c
n
c
m
1
0
4
7
4
6
2
0
3
4
1
4
1
2
6
6
1
8
9
6
8
8
4
9
BLP
sm
4
3
2
2
2
8
1
6
2
0
9
1
1
2
6
7
8
7
4
6
1
4
6
9
m
1
4
9
4
2
7
2
1
7
9
4
0
1
9
0
3
1
7
2
PO
L
m
-
0
0
0
0
-
0
0
-
0
0
-
0
0
-
0
0
m
1
8
8
1
6
2
3
4
5
0
3
1
9
4
6
1
2
0
1
5
6
0
4
2
BLP
Sm
1
3
5
0
4
6
2
4
3
4
2
7
5
6
3
8
1
7
1
8
4
8
3
5
m
1
6
9
2
1
5
4
2
7
9
5
4
2
1
5
3
1
7
2
PO
L
rn
-
0
0
0
0
-
0
0
-
0
0
-
0
0
-
0
0
m
2
2
1
3
9
8
6
2
8
8
6
3
1
4
9
8
4
4
3
2
9
6
7
8
BLP
sm
1
5
9
3
6
9
4
8
4
0
2
2
6
8
51
2
1
1
7
4
1
3
4
m
1
1
8
7
4
4
8
6
3
9
7
5
3
3
6
7
6
2
2
PO
L
m
-
0
0
0
0
-
0
0
-
0
0
-
0
0
-
0
0
m
2
6
1
7
7
8
7
1
5
8
5
0
1
6
1
8
2
2
3
8
7
8
7
6
BLP
s
9
8
8
5
6
7
5
5
5
4
5
7
7
0
6
7
2
0
3
8
6
2
5
5
m
1
1
0
4
3
0
3
3
2
9
9
7
2
1
3
5
4
3
2
PO
L
m
-
0
0
0
0
-
0
0
-
0
0
-
0
0
-
0
0
<
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m
r=3
BLP
s~
s=2
me
4
9
53
15
14
4
43
12
11
80
82
1
13
18
14
71
75
1
12
32
33
27
38
2
29
66
84
46
52
5
79
16
18
16
14
1
18
2POL
m
-
00
00
-
00
-
00
-
00
-
00
18
29
91
12
1
16
m
r=3
BLP
s~
s=3
m
46
62
31
50
2
33
28
2
0
10
14
1
25
10
17
61
15
8
18
6
0
8
5
14
2
2
5
78
24
43
31
47
1
26
2POL
m
-
00
00
-
00
-
00
-
00
-
00
26
33
28
31
9
19
4
6
61
15
2
6
4
67
16
12
76
13
1
13
42
60
30
59
2
40
12
2
3
92
19
1
1
m
r=4
BLP
s
s=2
me
12
23
27
47
5
87
2POL
m
-
00
00
-
00
-
00
-
00
-
00
2
2
47
14
29
2
41
58
17
35
66
4
90
10
27
57
12
9
2
6
m
r=4
BLP
s~
s=3
m
9
6
1
0
25
4
3
8
1
9
38
6
4
14
11
2
54
16
22
72
14
9
16
2POL
m
m
00
00
-
00
-
00
-
00
-
00
4
2
1
8
21
61
3
8
401
1
1
2
32
73
1
2
1
56
17
42
12
4
12
01
0.14
16
4
7
10
29
1
38
01
m
r=4
BLP
sm
s=4
m
4
8
1
1
11
41
4
9
901
2POL
m
12
48
10
37
1
33
01
Z O Q O ~
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Ta
e
6
D
P2
s
d
a
s
r 2
s=
1
r
=
2
s=
1
r
=
2
s
=
2
r
=
3
s=1
g gn
0
0
0
5I I 3
0
01
0I I 3
0
0
2
0
I 4 3
0
0
4
0I 4 3
0
0
8
0I
13
0
0
1
0I
13
n
c
n
c
n
c
n
c
n
c
n
c
m
1
0
6
9
3
8
1
4
2
4
1
9
8
4
4
9
1
0
6
7
8
2
4
8
BLP
sm
1
8
4
7
6
1
2
7
4
2
4
1
8
5
4
1
7
7
0
1
2
5
3
m
e
8
4
6
1
6
7
7
3
8
3
2
4
3
2
1
3
2
1
N
-PO
L
m
-
5
2
5
2
-
5
2
-
5
2
5
2
-
5
2
m
4
2
2
5
1
8
7
5
1
8
6
6
2
2
1
3
5
6
3
4
1
6
7
8
BLP
sm
2
3
1
5
1
2
1
3
1
8
6
5
5
4
3
9
5
7
3
5
1
6
1
3
m
2
1
6
5
3
5
4
2
6
7
6
6
2
2
9
3
2
6
N
-PO
L
m
-
8
8
8
8
m
8
8
-
8
8
8
8
-
8
8
m
6
4
4
8
1
8
8
5
1
4
1
5
2
6
1
5
7
8
6
7
1
0
1
4
BLP
sm
4
5
3
3
8
8
6
1
1
4
9
5
3
7
2
6
6
4
4
1
1
6
1
4
m
3
2
0
8
6
8
1
1
6
1
1
6
6
5
9
3
4
1
N
-PO
L
m
-
1
9
1
9
-
1
9
-
1
9
1
9
-
1
9
m
5
4
5
8
1
4
1
6
8
6
8
4
5
4
7
1
2
4
2
4
3
2
4
2
BLP
sm
4
1
4
7
9
0
9
0
8
4
8
7
4
1
4
7
2
1
2
9
1
8
2
0
m
e
4
3
8
6
6
4
4
4
4
3
4
7
1
1
5
3
3
8
N
-PO
L
m
-
2
2
-
2
2
-
2
2
-
2
2
-
2
2
-
2
2
O g
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m
r
=
3
BLP
Sm
S
=
2
me
N
-PO
L
rn
m
r
=
3
BLP
sm
s
=
3
me
N
-PO
L
m
m
r
=
4
BLP
sm
s
=
2
me
N
-PO
L
m
1
9
1
7
1
1
1
2
1
1
1
2
4
3
5
2
6
3
2
1
1
0
-
3
9
2
2
3
4
1
1
2
5
1
2
4
-
3
9
6
2
1
6
2
7
4
2
7
1
1
2
6
2
6
1
5
2
8
1
2
8
3
9
9
8
1
4
6
2
9
2
6
1
2
1
2
1
2
3
m
r
=
4
BLP
sm
s
=
3
me
9
2
9
3
5
1
3
1
0
7
7
3
9
1
2
1
1
9
0
7
2
1
8
7
3
9
3
3
5
0
-
3
9
4
4
7
3
2
7
4
4
3
5
9
6 0
5 8
3
4
8
5
2
1
9
9
8
6
4
7
3
9
7
3
9
0
3
4
-
6
7
-
6
7
6
7
6
7
-
6
7
-
6
7
1
0
1
4
3
0
5
1
3
2
5
4
4
8
8
9
1
2
1
1
2
0
3
9
6
5
9
7
2
8
3
1
3
8
5
4
6
5
9
9
9
6
1
1
3
6
6
0
8
1
3
2
4
8
2
3
3
2
3
0
7
1
2
9
1
3
7
9
-
7
9
-
7
9
-
7
9
-
7
9
7
9
7
2
1
2
1
4
2
2
2
5
1
7
2
1
1
4
0
8
7
5
1
0
4
4
8
2
1
0
2
3
4
8
4
8
1
1
0
4
3
9
1
6
1
9
N
-PO
L
m
9
8
-
9
8
-
9
8
9
8
1
4
2
3
1
7
2
6
5
1
9
2
0
6
9
1
3
4
0
1
4
5
1
2
3
4
1
4
3
0
5
1
9
m
r
=
4
BLP
Sm
S
=
4
me
9
0
2
8
5
0
1
2
7
1
1
9
8
9
8
4
8
1
3
1
8
5
6
3
4
9
2
2
0
7
4
3
9
4
9
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544 P. Marcotte and G. Savard
Fina lly i t would be interest ing to co mpar e the practical performance of the
proposed bi level prog ramm ing approac h to that of more es tabl ished methods of
global optimizat ion, such as the cutt in g-plan e meth ods of Horst an d T uy [12].
Acknowledgments: We would like to thank Grrald Marquis and Xavier Haurie for their help in
conducting the numerical experiments.
eferences
[1] Bajgier SM and Hill AV 1982) An experimental comparison of statistical and linear program-
ming approaches to the discriminant problem. Decision Sciences 13:604-618
[2] Bodlaender HL, Gritzmann P, Klee V and Van Leeuwen J 1990) Computational complexity
of norm-maximization.Combinatorica 10:203-225
[3] Cavalier TM, Ignizio JP and Soyster AL 1989) Discriminant analysis via mathematical pro-
gramming: certain problems and their causes.Com puters and Operations Research 16:353-362
[4] Fisher R A 19 36) Th e use of mu l t ip le measure men ts in taxono mic problems. Annals o f Eugenics
7:179-188
[5] Freed N and Glover F 1981) A linear programming approach to the discriminant problem.Decision Sciences 12:68-74
[6] Freed N and Glover F 1981) Simple but powerful goal programming models for discriminant
problems. European Journal of Operational Research 7:44-60
[7] Freund RM and Orlin JB 1985) On the complexity of four polyhedral set containment
problems. Mathematical Programming 33:139-145
I-8] Garey MR and Johnson DS 1979)Computers and intactahility, Freeman WH, San Francisco
[9] Gaither N and Glorfeld W 1982) On using linear programming in discriminant problems.
Decision Sciences 13:167-171
[10] Glover F 1990) Improved linear programming models for discriminant analysis. Decision
Sciences 21 : 771-785
[11] Hansen P, Jaumard B and Savard G 1990) New branch-and-bound rules for linear bilevel
programming, Cahier du GERAD G-89-09. Ecole Polytechnique, Montrral, submitted forpublication
[12] Horst R and Tuy H 1990) Global optimization. Deterministic approaches. Springer-Verlag,
New-York
[13] Johnson DS and Preparata FP 1978) The densest hemisphere problem. Theoretical Computer
Science 6: 93 - 107
[14] Kojima M, Mizuno S and Noma T. A polynomial-time algorithm for a class of linear comple-mentarity problems, to appear in Mathematical Programming
[15] Khachyan LG 1979) A polynomial algorithm in linear programming in Russian),Doklady
Akademi ia Nauk SSSR 244:1093-1096; English translation: Soviet Mathematics Doklady 20:191-194
[16] Koehler GJ 1989) Characterization of unacceptable solutions in LP discriminant analysis.Decision Sciences 20: 239-257
[17] Koehler GJ and Erenguc SS 1990) Minimizing misclassifications in linear discriminantanalysis.Decision Sciences 21:63-85
[18] Konno H 1976) Maximization of a convex quadratic function subject to linear constraints.Mathematical Programming 11 : 117-127
8/12/2019 Novel Approaches Discrimination
http://slidepdf.com/reader/full/novel-approaches-discrimination 29/29
No v e l Ap p r o a c h es t o t h e D i s c r im in a t i o n P r o b l e m 5 45
[19] L in YY a nd Pan g JS (1987) I te ra t ive me thods fo r large convex quadra t ic p rograms: a su rvey .
S I M Journal on Control and Optimization 2 5 :3 8 3 - 4 1 1
[20] M arkow sk i CA an d M arkow sk i EP (1987) An exper imen ta l com par ison o f severa l approaches
to t h e d i s c r im in a n tp rob le m w i th bo th qua l i ta t ive and quan t i ta t ive var iab les . European Journalo f O perational Research 2 8 : 7 4 - 7 8
[ 2 1 ] Ru b in P A ( 19 8 9) E v a lu a t in g t he m a x im iz e m in im u m d i s ta n c e f o r m u la t i o n o f t h e l i n e a r
d i s c r im in a n t p r o b le m . European Journal o f Operational Research 4 1 :2 4 0 - 2 4 8
[22] S tam A a nd Joach im stha le r EA (1990) A com par ison o f a rob us t mixed- in teger approach to
exist ing m etho ds for e stablishing classif ication rules for the disc r im inan t problem . European
Journal o f O perational Research 4 6 : 1 1 3 - 2 2
[23] Wolfe P (1976) Fin din g he nearest point in a polytope. Mathem atical Programming 11 : 128-14 9
Received: Fe bru ary 1991
Revised ve rsion received: Octo ber 1991