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8/16/2019 CSC 3301-Lecture06 Introduction to Machine Learning
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INTRODUCTION TO
MACHINE LEARNING
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A Few Quotes
• “A breakthrough in machine earning !ou" be !orthten Micro#o$t#% &'i Gate#( Chairman( Micro#o$t)
• “Machine earning i# the ne*t Internet%&Ton+ Tether( Director( DAR,A)
• Machine earning i# the hot ne! thing%&-ohn Henne##+( ,re#i"ent( .tan$or")
• “/eb ranking# to"a+ are mo#t+ a matter o$ machineearning% &,rabhakar Ragha0an( Dir1 Re#earch( 2ahoo)
•“Machine earning i# going to re#ut in a rea re0oution%&Greg ,a3a"o3ouo#( CTO( .un)
• “Machine earning i# to"a+4# "i#continuit+%&-err+ 2ang( CEO( 2ahoo)
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De$inition#
• Machine earning in0e#tigate# the mechani#m# b+ !hich
kno!e"ge i# ac5uire" through e*3erience
• Machine Learning i# the $ie" that concentrate# on
in"uction agorithm# an" on other agorithm# that can be
#ai" to 66earn177
• Learning through the "ata #et#
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Mo"e
• A mo"e o$ earning i# $un"amenta in an+ machine
earning a33ication8• !ho i# earning &a com3uter 3rogram)
• !hat i# earne" &a "omain)
• $rom !hat the earner i# earning &the in$ormation #ource)
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Traditional Programming
Machine Learning
ComputerData
ProgramOutput
ComputerData
OutputProgram
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Magic?
No, more like gardening
• Seeds 9 Agorithm#
• Nutrients 9 Data
• Gardener 9 2ou
• Plants 9 ,rogram#
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Sample Applications
• /eb #earch• Com3utationa bioog+• :inance
• E;commerce• .3ace e*3oration• Robotic#• In$ormation e*traction
• .ocia net!ork#• Debugging•
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ML in a Nutshell
• Ten# o$ thou#an"# o$ machine earning agorithm#
• Hun"re"# ne! e0er+ +ear
• E0er+ machine earning agorithm ha# three com3onent#8•
epresentation• !"aluation
• #ptimi$ation
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epresentation
• Deci#ion tree#• .et# o$ rue# > Logic 3rogram#• In#tance#• Gra3hica mo"e# &'a+e#>Marko0 net#)• Neura net!ork#• .u33ort 0ector machine#• Mo"e en#embe#• Etc1
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!"aluation
• Accurac+• ,reci#ion an" reca• .5uare" error
• Likeihoo"• ,o#terior 3robabiit+• Co#t > Utiit+• Margin
• Entro3+• ?;L "i0ergence• Etc1
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#ptimi$ation
• Combinatoria o3timi@ation• E1g18 Gree"+ #earch
• Con0e* o3timi@ation• E1g18 Gra"ient "e#cent
• Con#traine" o3timi@ation• E1g18 Linear 3rogramming
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Data ,re3aration
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Data ,re3roce##ing
• /h+ 3re3roce## the "ata
• Data ceaning
• Data integration an" tran#$ormation
• Data re"uction
• Di#creti@ation an" conce3t hierarch+ generation
• .ummar+
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/h+ Data ,re3roce##ing
• Data in the rea !or" i# "irt+• incom3ete8 acking attribute 0aue#( acking certain
attribute# o$ intere#t( or containing on+ aggregate "ata
• noi#+8 containing error# or outier#• incon#i#tent8 containing "i#cre3ancie# in co"e# or
name#
• No 5uait+ "ata( no 5uait+ mining re#ut#B• uait+ "eci#ion# mu#t be ba#e" on 5uait+ "ata
• Data !arehou#e nee"# con#i#tent integration o$ 5uait+
"ata
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Maor Ta#k# in Data ,re3roce##ing
• Data ceaning• :i in mi##ing 0aue#( #mooth noi#+ "ata( i"enti$+ or remo0e outier#( an"
re#o0e incon#i#tencie#
• Data integration
• Integration o$ muti3e "ataba#e#( "ata cube#( or $ie#
• Data tran#$ormation• Normai@ation an" aggregation
• Data re"uction
• Obtain# re"uce" re3re#entation in 0oume but 3ro"uce# the #ame or#imiar ana+tica re#ut#
• Data "i#creti@ation• ,art o$ "ata re"uction but !ith 3articuar im3ortance( e#3ecia+ $or
numerica "ata
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:orm# o$ "ata 3re3roce##ing
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Data ,re3roce##ing
• /h+ 3re3roce## the "ata
• Data ceaning
• Data integration an" tran#$ormation
• Data re"uction
• Di#creti@ation an" conce3t hierarch+ generation
• .ummar+
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Data Ceaning
• Data ceaning ta#k#
• :i in mi##ing 0aue#
• I"enti$+ outier# an" #mooth out noi#+ "ata
• Correct incon#i#tent "ata
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Mi##ing Data
• Data i# not a!a+# a0aiabe
• E1g1( man+ tu3e# ha0e no recor"e" 0aue $or #e0era attribute#(
#uch a# cu#tomer income in #ae# "ata
• Mi##ing "ata ma+ be "ue to• e5ui3ment ma$unction
• incon#i#tent !ith other recor"e" "ata an" thu# "eete"
• "ata not entere" "ue to mi#un"er#tan"ing
• certain "ata ma+ not be con#i"ere" im3ortant at the time o$ entr+
• not regi#ter hi#tor+ or change# o$ the "ata
• Mi##ing "ata ma+ nee" to be in$erre"1
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Ho! to Han"e Mi##ing Data
• Ignore the tu3e8 u#ua+ "one !hen ca## abe i# mi##ing &a##uming
the ta#k# in ca##i$icationnot e$$ecti0e !hen the 3ercentage o$
mi##ing 0aue# 3er attribute 0arie# con#i"erab+)
• :i in the mi##ing 0aue manua+8 te"iou# F in$ea#ibe
• U#e a goba con#tant to $i in the mi##ing 0aue8 e1g1( “unkno!n%( a
ne! ca##B
• U#e the attribute mean to $i in the mi##ing 0aue
• U#e the mo#t 3robabe 0aue to $i in the mi##ing 0aue8 in$erence;
ba#e" #uch a# 'a+e#ian $ormua or "eci#ion tree
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Noi#+ Data
• Noi#e8 ran"om error or 0ariance in a mea#ure" 0ariabe
• Incorrect attribute 0aue# ma+ "ue to
• $aut+ "ata coection in#trument#
• "ata entr+ 3robem#
• "ata tran#mi##ion 3robem#• technoog+ imitation
• incon#i#tenc+ in naming con0ention
• Other "ata 3robem# !hich re5uire# "ata ceaning
•"u3icate recor"#
• incom3ete "ata
• incon#i#tent "ata
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Ho! to Han"e Noi#+ Data
• 'inning metho"8• $ir#t #ort "ata an" 3artition into &e5ui;"e3th) bin#
• then #mooth b+ bin mean#( #mooth b+ bin me"ian(
#mooth b+ bin boun"arie#( etc1• Cu#tering
• "etect an" remo0e outier#
• Combine" com3uter an" human in#3ection• "etect #u#3iciou# 0aue# an" check b+ human
• Regre##ion• #mooth b+ $itting the "ata into regre##ion $unction#
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Data ,re3roce##ing
• /h+ 3re3roce## the "ata
• Data ceaning
• Data integration an" tran#$ormation
• Data re"uction
• Di#creti@ation an" conce3t hierarch+ generation
• .ummar+
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Data Integration
• Data integration8• combine# "ata $rom muti3e #ource# into a coherent #tore
• .chema integration
• integrate meta"ata $rom "i$$erent #ource#• Entit+ i"enti$ication 3robem8 i"enti$+ rea !or" entitie#
$rom muti3e "ata #ource#( e1g1( A1cu#t;i" ≡ '1cu#t;
• Detecting an" re#o0ing "ata 0aue con$ict#•
$or the #ame rea !or" entit+( attribute 0aue# $rom"i$$erent #ource# are "i$$erent• 3o##ibe rea#on#8 "i$$erent re3re#entation#( "i$$erent
#cae#( e1g1( metric 0#1 'riti#h unit#
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Han"ing Re"un"ant Data
• Re"un"ant "ata occur o$ten !hen integration o$ muti3e
"ataba#e#
• The #ame attribute ma+ ha0e "i$$erent name# in "i$$erent
"ataba#e#• Care$u integration o$ the "ata $rom muti3e #ource#
ma+ he3 re"uce>a0oi" re"un"ancie# an"
incon#i#tencie# an" im3ro0e mining #3ee" an" 5uait+
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Data Tran#$ormation
• .moothing8 remo0e noi#e $rom "ata
• Aggregation8 #ummari@ation( "ata cube con#truction
• Generai@ation8 conce3t hierarch+ cimbing
• Normai@ation8 #cae" to $a !ithin a #ma( #3eci$ie"
range
• min;ma* normai@ation
• @;#core normai@ation
• normai@ation b+ "ecima #caing
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Data Tran#$ormation8
Normai@ation
• min;ma* normai@ation
• @;#core normai@ation
• normai@ation b+ "ecima #caingWhere j is the smallest integer such that Max(| |)
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Data ,re3roce##ing
• /h+ 3re3roce## the "ata
• Data ceaning
• Data integration an" tran#$ormation
• Data re"uction
• Di#creti@ation an" conce3t hierarch+ generation
• .ummar+
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Data Re"uction .trategie#
• /arehou#e ma+ #tore terab+te# o$ "ata8 Com3e*
"ata ana+#i#>mining ma+ take a 0er+ ong time to run
on the com3ete "ata #et
• Data re"uction• Obtain# a re"uce" re3re#entation o$ the "ata #et that i#
much #maer in 0oume but +et 3ro"uce# the #ame &or
amo#t the #ame) ana+tica re#ut#
• Data re"uction #trategie#• Data cube aggregation
• Dimen#ionait+ re"uction
• Numero#it+ re"uction
• Di#creti@ation an" conce3t hierarch+ generation
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Data Cube Aggregation
• The o!e#t e0e o$ a "ata cube
• the aggregate" "ata $or an in"i0i"ua entit+ o$ intere#t
• e1g1( a cu#tomer in a 3hone caing "ata !arehou#e1
• Muti3e e0e# o$ aggregation in "ata cube#
• :urther re"uce the #i@e o$ "ata to "ea !ith
• Re$erence a33ro3riate e0e#
• U#e the #mae#t re3re#entation !hich i# enough to #o0e
the ta#k
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Dimen#ionait+ Re"uction
• :eature #eection &i1e1( attribute #ub#et #eection)8
• .eect a minimum #et o$ $eature# #uch that the
3robabiit+ "i#tribution o$ "i$$erent ca##e# gi0en
the 0aue# $or tho#e $eature# i# a# co#e a#3o##ibe to the origina "i#tribution gi0en the
0aue# o$ a $eature#
• re"uce o$ 3attern# in the 3attern#( ea#ier to
un"er#tan"
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.am3ing
• Ao! a mining agorithm to run in com3e*it+ that i#
3otentia+ #ub;inear to the #i@e o$ the "ata
• Choo#e a re3re#entati0e #ub#et o$ the "ata
• .im3e ran"om #am3ing ma+ ha0e 0er+ 3oor3er$ormance in the 3re#ence o$ #ke!
• De0eo3 a"a3ti0e #am3ing metho"#
• .trati$ie" #am3ing8
• A33ro*imate the 3ercentage o$ each ca## &or #ub3o3uation o$ intere#t)in the o0era "ataba#e
• U#e" in conunction !ith #ke!e" "ata
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Sampling
S R S W O R
( s i m p l e r a n d o m
s a m p l e i
t h o u t
r e p l a c e m e
n t )
S R S W R
Ra !ata
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Data ,re3roce##ing
• /h+ 3re3roce## the "ata
• Data ceaning
• Data integration an" tran#$ormation
• Data re"uction
• Di#creti@ation an" conce3t hierarch+ generation
• .ummar+
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Di#creti@ation
• Three t+3e# o$ attribute#8• Nomina 0aue# $rom an unor"ere" #et• Or"ina 0aue# $rom an or"ere" #et• Continuou# rea number#
• Di#creti@ation8• "i0i"e the range o$ a continuou# attribute into inter0a#• .ome ca##i$ication agorithm# on+ acce3t categorica
attribute#1• Re"uce "ata #i@e b+ "i#creti@ation• ,re3are $or $urther ana+#i#
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Di#creti@ation an" Conce3t hierach+
• Di#creti@ation
• re"uce the number o$ 0aue# $or a gi0en continuou#
attribute b+ "i0i"ing the range o$ the attribute into
inter0a#1 Inter0a abe# can then be u#e" to re3ace
actua "ata 0aue#1
• Conce3t hierarchie#
• re"uce the "ata b+ coecting an" re3acing o! e0econce3t# uch a# numeric 0aue# $or the attribute age)
b+ higher e0e conce3t# uch a# +oung( mi""e;age"(
or #enior)1
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Data ,re3roce##ing
• /h+ 3re3roce## the "ata
• Data ceaning
• Data integration an" tran#$ormation
• Data re"uction
• Di#creti@ation an" conce3t hierarch+ generation
• .ummar+
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.ummar+
• Data 3re3aration i# a big i##ue $or both !arehou#ing
an" mining
• Data 3re3aration incu"e#
• Data ceaning an" "ata integration
• Data re"uction an" $eature #eection
• Di#creti@ation• A ot a metho"# ha0e been "e0eo3e" but #ti an acti0e
area o$ re#earch
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Re$erence#
• D1 ,1 'aou an" G1 ?1 Ta+i1 Enhancing "ata 5uait+ in "ata !arehou#e
en0ironment#1 Communication# o$ ACM( 8JK;J( 1
• -aga"i#h et a1( .3ecia I##ue on Data Re"uction Techni5ue#1 'uetin o$ the
Technica Committee on Data Engineering( &)( December J1
• D1 ,+e1 Data ,re3aration $or Data Mining1 Morgan ?au$mann( 1
• T1 Re"man1 Data uait+8 Management an" Technoog+1 'antam 'ook#(
Ne! 2ork( 1
• 21 /an" an" R1 /ang1 Anchoring "ata 5uait+ "imen#ion# ontoogica
$oun"ation#1 Communication# o$ ACM( K8P;Q( P1
• R1 /ang( 1 .tore+( an" C1 :irth1 A $rame!ork $or ana+#i# o$ "ata 5uait+
re#earch1 IEEE Tran#1 ?no!e"ge an" Data Engineering( J8PK;P( Q1
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T%pes o& Learning
• Super"ised 'inducti"e( learning• Training "ata incu"e# "e#ire" out3ut#
• )nsuper"ised learning• Training "ata "oe# not incu"e "e#ire" out3ut#
• Semi*super"ised learning• Training "ata incu"e# a $e! "e#ire" out3ut#
• ein&orcement learning• Re!ar"# $rom #e5uence o$ action#
41
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De#igning a Learning .+#tem8
An E*am3e
1 ,robem De#cri3tion 8 Ca##i$+ing cancer
1 Choo#ing the Training E*3erience8 Data Coection
K1 Choo#ing the Target :unction > target out3ut8 I"enti$+
a33ro3riate $unction $or the "ata1 Choo#ing a :unction Agorithm
P1 De#ign
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Data Coection
• htt38>>archi0e1ic#1uci1e"u>m>
• +reast ancer -isconsin '#riginal( .ata Set
• Attribute Domain ;; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; 1 .am3e co"e number i"
number 1 Cum3 Thickne## ; K1 Uni$ormit+ o$ Ce .i@e ; 1 Uni$ormit+ o$
Ce .ha3e ; Q1 Margina A"he#ion ; P1 .inge E3itheia Ce .i@e ; J1
'are Nucei ; 1 'an" Chromatin ; 1 Norma Nuceoi ; 1 Mito#e# ;
1 Ca##8 & $or benign( $or maignant)
• Q(Q((((((K((( Q(Q(((Q(J((K((( QQ(K((((((K(((
PJJ(P((((K((K(J(( JK((((K(((K(((
J(((((J(((J(( (((((((K(((
QP(((((((K((( KKJ(((((((((Q( KKJ((((((((((
KQK(((((((K((( KPJ(((((((((( (Q(K(K(K((K((((K((((((K(K((( QJ((J(Q((J((Q(Q(( JPK(J((P((P(((K((
PJ(((((((((( Q(((((((K(((
QPJ((J(J(P(((((( QJ(P((((((K(((
• Ca## "i#tribution8 'enign8 Q &PQ1QS) Maignant8 &K1QS)
http://archive.ics.uci.edu/ml/http://archive.ics.uci.edu/ml/http://archive.ics.uci.edu/ml/
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Choo#ing a :unction Agorithm
• A33+ing to Neura Net!ork• In3ut Data
• Number o$ a+er#
• Out3ut Data
• De#ign• Training Data
• Te#ting Data
.te3#
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,re"iction
.te3#
Training
Labe#Training
Image#
Training
Training
Image
:eature#
Image
:eature#
Testing
Te#t Image
Learne"
mo"e
Learne"
mo"e
Slide credit: D. Hoiem and L.
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Cro## 0ai"ation
• .oution8 k;$o" cro## 0ai"ation ma*imi@e# the u#e o$the "ata1
• Di0i"e "ata ran"om+ into k $o"# ub#et#) o$ e5ua#i@e1
• Train the mo"e on k $o"#( u#e one $o" $or te#ting1• Re3eat thi# 3roce## k time# #o that a $o"# are u#e"$or te#ting1
• Com3ute the a0erage 3er$ormance on the k te#t #et#1
• Thi# e$$ecti0e+ u#e# a the "ata $or both training an"te#ting1
• T+3ica+ k 9 i# u#e"1
• .ometime# #tratie" k;$o" cro## 0ai"ation i# u#e"1
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Cro## 0ai"ation
• I"enti$+ n “$o"#% o$ the a0aiabe "ata1• Train on n-1 $o"#• Te#t on the remaining $o"1
• In the e*treme &n=N ) thi# i# kno!n a#“lea"e*one*out% cro## 0ai"ation
47
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48
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• In k ;$o" cro##;0ai"ation( the origina #am3e i# ran"om+ 3artitione"
into k #ub#am3e#1 O$ the k #ub#am3e#( a #inge #ub#am3e i#
retaine" a# the 0ai"ation "ata $or te#ting the mo"e( an" the
remaining k #ub#am3e# are u#e" a# training "ata1 The cro##;
0ai"ation 3roce## i# then re3eate" k time# &the folds)( !ith each o$
the k #ub#am3e# u#e" e*act+ once a# the 0ai"ation "ata1 The k
re#ut# $rom the $o"# then can be a0erage" &or other!i#e combine")
to 3ro"uce a #inge e#timation1 The a"0antage o$ thi# metho" o0erre3eate" ran"om #ub;#am3ing i# that a ob#er0ation# are u#e" $or
both training an" 0ai"ation( an" each ob#er0ation i# u#e" $or
0ai"ation e*act+ once1 ;$o" cro##;0ai"ation i# common+ u#e"(
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/*&old cross*"alidation
Thi# i# the #im3e#t 0ariation o$ k ;$o" cro##;0ai"ation1
:or each $o"( !e ran"om+ a##ign "ata 3oint# to t!o
#et# d an" d ( #o that both #et# are e5ua #i@e &thi# i#
u#ua+ im3emente" a# #hu$$ing the "ata arra+ an"
then #3itting in t!o)1 /e then train on d an" te#t ond ( $oo!e" b+ training on d an" te#ting on d 1
Thi# ha# the a"0antage that our training an" te#t #et#
are both arge( an" each "ata 3oint i# u#e" $or both
training an" 0ai"ation on each $o"1
50
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Lea"e*one*out cross*"alidation
• Lea0e;one;out cro##0ai"ation i# #im3+ k;$o"
cro##0ai"ation !ith k #et to n( the number o$in#tance# in the "ata #et1
• Thi# mean# that the te#t #et on+ con#i#t# o$ a #inge
in#tance( !hich !i be ca##ie" either correct+ or
incorrect+1
• A"0antage#8 ma*ima u#e o$ training "ata( i1e1(
training on n in#tance#1 The 3roce"ure i#
"etermini#tic( no #am3ing in0o0e"1
• Di#a"0antage#8 un$ea#ibe $or arge "ata #et#8 arge
number o$ training run# re5uire"( high com3utationaco#t1 Cannot be #tratie" &on+ one ca## in the te#t
#et)1
01
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Cro##;0ai"ation 0i#uai@e"
A0aiabe Labee" Data
I"enti$+ n 3artition#
Train Train Train Train De0 Te#t:o"
0/
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Cro##;0ai"ation 0i#uai@e"
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