8 Machine Learning
-
Upload
minotoji-mi -
Category
Documents
-
view
24 -
download
0
description
Transcript of 8 Machine Learning
-
Gii thiu hc my
Ng Xun Bch
Hc vin Cng ngh Bu chnh Vin thng Khoa Cng ngh thng tin 1
Nhp mn tr tu nhn to
-
Ni dung
http://www.ptit.edu.vn 2
Gii thiu
Hc cy quyt nh
Phn loi Bayes n gin
Hc da trn v d
-
Ti liu tham kho
http://www.ptit.edu.vn 3
N. Nilsson. Introduction to machine learning http://ai.stanford.edu/people/nilsson/mlbook.html
T. Mitchell. Machine learning. McGraw-Hill, 1997.
E. Alpaydin. Introduction to machine learning. MIT Press, 2004.
M. Mohri, A. Rostamizadeh, A. Talwalkar. Foundations of Machine Learning. MIT Press, 2012.
-
Cng c v d liu
http://www.ptit.edu.vn 4
B cng c Weka o http://www.cs.waikato.ac.nz/~ml/weka
Kho d liu mu UC Irvine o http://www.ics.uci.edu/~mlearn/ML/Repository.html
-
Mt s ng dng ca hc my (1/3)
http://www.ptit.edu.vn 5
Nhng ng dng kh lp trnh theo cch thng thng do khng tn ti hoc kh gii thch kinh nghim, k nng ca con ngi o Nhn dng ch vit, m thanh, hnh nh
o Li xe t ng, thm him sao Ho
Chng trnh my tnh c kh nng thch nghi: li gii thay i theo thi gian hoc theo tnh hung c th o Chng trnh tr gip c nhn
o nh tuyn mng
-
Mt s ng dng ca hc my (2/3)
http://www.ptit.edu.vn 6
Khai ph (phn tch) d liu o H s bnh n tri thc y hc
o D liu bn hng quy lut kinh doanh
-
Mt s ng dng ca hc my (3/3)
http://www.ptit.edu.vn 7
Hu ht cc ng dng tr tu nhn to ngy nay c s dng hc my
-
Hc my l g?
http://www.ptit.edu.vn 8
Hc: o thu thp kin thc hoc k nng
Hc my: o Gii quyt vn t kinh nghim
o c thc hin bi chng trnh my tnh c kh nng: Thc hin cng vic tt hn
Theo tiu ch
Nh s dng d liu mu hoc kinh nghim
-
V d
http://www.ptit.edu.vn 9
Hc nh c o : nh c
o : s vn thng
o : kinh nghim t chi
Hc nhn dng ch o : nhn dng ch ci t nh
o : phn trm ch nhn dng ng
o : nh s ca ch v ch tng ng
Dch my o : dch mt cu ting Anh sang ting Vit
o : o dch my (v d s cu ng, s mnh ng,)
o : cp cu ting Anh v ting Vit tng ng
-
Vn cn quan tm (1/2)
http://www.ptit.edu.vn 10
Kinh nghim c th nh th no? o Kinh nghim trc tip v gin tip
Trc tip: trng thi c th + nc i ng tng ng
Gin tip: ton b vn c v kt qu
o C gim st (hng dn) v khng gim st C gim st
Khng gim st
Bn gim st
Cn phi hc ci g? Biu din kin thc hc c th no?
o Tri thc cn hc c biu din nh mt hm ch, cn la chn hm ch c th
o V d nh c:
Chn_nc_i:
im_s:
-
Vn cn quan tm (2/2)
http://www.ptit.edu.vn 11
S dng thut ton g hc? o S dng hm
VD: _ = 11+22+ 33+ 44+
o S dng cc lut
o S dng mng n ron
o S dng cy quyt nh
o S dng cc m hnh xc sut
o
-
Thit k chng trnh hc my
http://www.ptit.edu.vn 12
La chn d liu hoc kinh nghim
La chn hm ch
La chn biu din cho hm ch
La chn thut ton hc
Tin hnh hc (hun luyn)
-
Mt s khi nim
http://www.ptit.edu.vn 13
Mu, hay v d (samples): l i tng cn x l (v d phn loi) o V d: khi lc th rc th mi th l mt mu
Mu thng c m t bng tp thuc tnh hay c trng (features) o V d: trong chun on bnh, thuc tnh l triu chng ca ngi
bnh, v cc tham s khc nh chiu cao, cn nng,
Nhn phn loi (label): th hin loi ca i tng m ta cn d on o V d: nhn phn loi th rc c th l rc hoc bnh thng
-
Mt s dng hc my ph bin
http://www.ptit.edu.vn 14
Hc c gim st (supervised learning) o Phn lp (classification)
o Hi quy (regression)
Hc khng gim st (unsupervised learning) o Hc lut kt hp (association)
o Phn cm (clustering)
Hc tng cng (reinforcement learning)
-
Phn lp
http://www.ptit.edu.vn 15
chiu cao
cn nng
-
Hi quy (regression)
http://www.ptit.edu.vn 16
Ti sn
Tui th = +
ng dng: d on gi c, li xe,
-
Hc lut kt hp
http://www.ptit.edu.vn 17
V d o Phn tch giao dch, mua bn (ha n mua hng)
(|) o Xc sut ngi mua hng cn mua hng
V d lut kt hp o Ngi mua bnh m thng mua b
o Ngi mua lc rang thng mua bia
-
Phn cm
http://www.ptit.edu.vn 18
Nhm nhng trng hp tng t vi nhau
Khng c gi tr u ra
ng dng o Phn cm khch hng, phn cm sinh vin
o Phn on nh
o Thit k vi mch
-
Hc tng cng
http://www.ptit.edu.vn 19
Kinh nghim khng c cho trc tip di dng u vo / u ra
H thng nhn c mt gi tr thng (reward) l kt qu cho mt chui hnh ng no
Thut ton cn hc cch hnh ng cc i ha gi tr thng
V d: hc nh c o H thng khng c ch cho nc i no l hp l cho tng tnh
hung c th
o Ch bit kt qu thng thua sau mt chui nc i
-
Ni dung
http://www.ptit.edu.vn 20
Gii thiu
Hc cy quyt nh (decision tree learning)
Phn loi Bayes n gin
Hc da trn v d
-
D liu hun luyn
http://www.ptit.edu.vn 21
Ngy Tri Nhit m Gi Chi tennis D1 nng nng cao yu khng
D2 nng nng cao mnh khng
D3 u m nng cao yu c
D4 ma trung bnh cao yu c
D5 ma lnh bnh thng yu c
D6 ma lnh bnh thng mnh khng
D7 u m lnh bnh thng mnh c
D8 nng trung bnh cao yu khng
D9 nng lnh bnh thng yu c
D10 ma trung bnh bnh thng yu c
D11 nng trung bnh bnh thng mnh c
D12 u m trung bnh cao mnh c
D13 u m nng bnh thng yu c
D14 ma trung bnh cao mnh khng
-
http://www.ptit.edu.vn 22
Ngy Tri Nhit m Gi Chi tennis D1 nng nng cao yu khng
D2 nng nng cao mnh khng
D3 u m nng cao yu c
D4 ma trung bnh cao yu c
D5 ma lnh bnh thng yu c
D6 ma lnh bnh thng mnh khng
D7 u m lnh bnh thng mnh c
D8 nng trung bnh cao yu khng
D9 nng lnh bnh thng yu c
D10 ma trung bnh bnh thng yu c
D11 nng trung bnh bnh thng mnh c
D12 u m trung bnh cao mnh c
D13 u m nng bnh thng yu c
D14 ma trung bnh cao mnh khng
thuc tnh nhn
mu
-
D liu
http://www.ptit.edu.vn 23
n mu hun luyn, mi mu l mt cp < , > o l vector cc thuc tnh
o l nhn phn loi, (tp cc nhn)
V d mu D4 o = , , ,
o =
-
V d cy quyt nh
http://www.ptit.edu.vn 24
Tri
m Gi C
khng c khng c
u m nng ma
bnh
thng mnh yu cao
-
Cy quyt nh l g?
http://www.ptit.edu.vn 25
L m hnh phn loi c dng cy o Mi nt trung gian (khng phi l) ng vi mt php kim tra
thuc tnh, mi nhnh ca nt ng vi mt gi tr ca thuc tnh ti nt
o Mi nt l ng vi mt nhn phn loi
Qu trnh phn loi thc hin nh sau
o Mu phn loi i t gc cy xung di o Ti mi nt trung gian, thuc tnh tng ng vi nt c kim
tra, ty gi tr thuc tnh, mu c chuyn xung nhnh tng ng
o Khi ti nt l, mu c nhn nhn phn loi ca nt
-
Biu din di dng quy tc
http://www.ptit.edu.vn 26
Cy quyt nh c th biu din tng ng di dng cc quy tc logic
Mi cy l tuyn ca cc quy tc, mi quy tc bao gm cc php hi
V d
(Tri = nng m = bnh_thng)
(Tri = u_m)
(Tri = ma Gi = yu)
-
Hc cy quyt nh
http://www.ptit.edu.vn 27
Cy quyt nh c hc (xy dng) t d liu hun luyn
Vi mi b d liu c th xy dng nhiu cy quyt nh o Chn cy no?
Qu trnh hc l qu trnh tm kim cy quyt nh ph hp vi d liu hun luyn o Cho php phn loi ng d liu hun luyn
-
Thut ton ID3
http://www.ptit.edu.vn 28
Xy dng ln lt cc nt ca cy bt u t gc
Thut ton o Khi u: nt hin thi l nt gc cha ton b tp d liu hun luyn o Ti nt hin thi , la chn thuc tnh
Cha c s dng nt t tin
Cho php phn chia tp d liu hin thi thnh cc tp con mt cch tt nht
Vi mi gi tr thuc tnh c chn thm mt nt con bn di
Chia cc v d nt hin thi v cc nt con theo gi tr thuc tnh c chn
o Lp ( quy) cho ti khi Tt c cc thuc tnh c s dng cc nt pha trn, hoc
Tt c v d ti nt hin thi c cng nhn phn loi
Nhn ca nt c ly theo a s nhn ca v d ti nt hin thi
La chn thuc tnh ti mi nt th no?
-
Tiu chun chn thuc tnh ca ID3
http://www.ptit.edu.vn 29
Ti mi nt o Tp (con) d liu ng vi nt
o Cn la chn thuc tnh cho php phn chia tp d liu tt nht
Tiu chun: o D liu sau khi phn chia cng ng nht cng tt
o o bng tng thng tin (Information Gain - IG)
o Chn thuc tnh c tng thng tin ln nht
o IG da trn entropy ca tp (con) d liu
-
Entropy
http://www.ptit.edu.vn 30
Trng hp tp d liu c 2 loi nhn: ng (+) hoc sai (-)
= ++ +: % s mu ng, : % s mu sai
Trng hp tng qut: c loi nhn
() =
=
: % v d ca thuc loi
V d (,
+, -) = (/)(/) (/)(/)
= .
-
tng thng tin IG
http://www.ptit.edu.vn 31
Vi tp (con) mu v thuc tnh
Trong :
values (A): tp cc gi tr ca
Sv l tp con ca bao gm cc mu c gi tr ca bng
|| s phn t ca
)(
)(||
||)(),(
Avaluesv
vv SEntropyS
SSEntropyASIG
-
V d tnh IG
http://www.ptit.edu.vn 32
Tnh ,
() = *,+
= 9+, 5 , = 9
1429
145
1425
14= 0.94
= 6+, 2 ,H = 6
826
82
822
8= 0.811
= 3+, 3 , H = 3
623
63
623
6= 1
, = 8
14H
6
14H
= 0.94 8
140.811
6
141
= 0.048
-
Cc c im ca ID3
http://www.ptit.edu.vn 33
ID3 l thut ton tm kim cy quyt nh ph hp vi d liu hun luyn
Tm kim theo kiu tham lam, bt u t cy rng
Hm nh gi l tng thng tin
ID3 c khuynh hng (bias) la chn cy n gin o t nt
o Cc thuc tnh c tng thng tin ln nm gn gc
-
Vn qu va d liu
http://www.ptit.edu.vn 34
qu va d liu nu tn ti sao cho
-
Chng qu va bng cch ta cy
http://www.ptit.edu.vn 35
Chia d liu thnh hai phn o Hun luyn
o Kim tra
To cy ln trn d liu hun luyn
Tnh chnh xc ca cy trn tp kim tra
Loi b cy con sao cho kt qu trn d liu kim tra c ci thin nht
Lp li cho n khi khng cn ci thin c kt qu na
-
Sau khi ta cy
http://www.ptit.edu.vn 36
-
Chng qu va d liu
bng cch ta lut (C4.5)
http://www.ptit.edu.vn 37
Bin i cy thnh cc lut
Ta mi lut c lp vi cc lut khc o B mt s phn trong v tri ca lut
Sp xp cc lut sau khi ta theo mc chnh xc ca lut
-
S dng thuc tnh c gi tr lin tc
http://www.ptit.edu.vn 38
To ra nhng thuc tnh ri rc mi
V d, vi thuc tnh lin lc , to ra thuc tnh ri rc nh sau o = nu A >
o = nu A
Xc nh ngng th no? o Thng chn sao cho em li tng thng tin ln nht
C th chia thnh nhiu khong vi nhiu ngng
-
Cc o khc
http://www.ptit.edu.vn 39
o Information Gain (IG) u tin thuc tnh c nhiu gi tr, v d, thuc tnh ngy s c tng thng tin cao nht
Thng tin chia
Tiu chun nh gi thuc tnh
S
S
S
SASmationSplitInfor
iic
i
2
1
log),(
),(
),(
ASmationSplitInfor
ASnGainInformatioGainRatio
-
Ni dung
http://www.ptit.edu.vn 40
Gii thiu
Hc cy quyt nh
Phn loi Bayes n gin (Nave Bayes classification)
Hc da trn v d
-
Phng php phn loi Bayes (1/2)
http://www.ptit.edu.vn 41
Trong giai on hun luyn ta c mt tp mu, mi mu c cho bi cp < , >, trong o l vector c trng (thuc tnh)
o l nhn phn loi, ( l tp cc nhn)
Sau khi hun luyn xong, b phn loi cn d on nhn cho mu mi =< 1, 2, , >
S dng quy tc Bayes
= (|1, 2, , )
= 1, 2, , | ()
(1, 2, , )
= 1, 2, , | ()
-
Phng php phn loi Bayes (2/2)
http://www.ptit.edu.vn 42
S dng gi thit v tnh c lp (n gin!!!)
= 1, 2, , | ()
Tn xut quan st thy nhn trn tp d liu D:
()
||
1, 2, , | = 1| 2| |
S ln xut hin cng vi chia
cho s ln xut hin : (,)
()
-
V d
http://www.ptit.edu.vn 43
Xc nh nhn phn loi cho mu sau < = , = , = , = >
= , = = = = ()
-
Ni dung
http://www.ptit.edu.vn 44
Gii thiu
Hc cy quyt nh
Phn loi Bayes n gin
Hc da trn v d (Instance based learning)
-
Nguyn tc chung
http://www.ptit.edu.vn 45
Khng xy dng m hnh
Ch lu li cc mu hun luyn
Xc nh nhn cho mu mi da trn nhng mu ging mu mi nht
Gi l hc li (lazy learning)
-
Thut ton hng xm gn nht
http://www.ptit.edu.vn 46
-nearest neighbors (-NN)
Chn mu ging mu cn phn loi nht, gi l hng xm
Gn nhn phn loi cho mu ch s dng thng tin ca hng xm ny
o V d ly theo a s trong s hng xm
Chn hng xm th no?
-
Tnh khong cch
http://www.ptit.edu.vn 47
Gi s mu c gi tr thuc tnh l < 1(), 2(), , () > , thuc tnh l s thc
Khong cch gia hai mu v l khong cch Euclidean instance
, = ( )2
=1
-
Thut ton -NN
http://www.ptit.edu.vn 48