L2-Gioi Thieu WEKA

7/22/2019 L2-Gioi Thieu WEKA

1/18

Khai Ph DLiu

([email protected])

Trng i hc Bch Khoa H Ni

Vin Cng ngh Thng tin v Truyn thng

Nm hc 2012-2013


2/18

Ni dung mn hc:

Gii thiu v Khai ph d liu

Gii thiu v cng c WEKA

Tin x l d liu

Pht hin cc lut kt hp

Cc k thut phn nhm

Lc cng tc

2Khai Ph DLiu


3/18

EKA Gii thiu WEKA l mt cng c phn mm vit bng Java, phc v

lnh vc hc my v khai ph d liu

Cc tnh nng chnh Mt tp cc cng c tin x l d liu, cc gii thut hc my,

,

Giao din ha (gm c tnh nng hin th ha d liu)

Mi trng cho php so snh cc gii thut hc my v khaip u

C th ti v t a ch:

. . . .

3Khai Ph DLiu


4/18

WEKA Cc mi trng chnh Simple CLI

ao n n g n u ng n n -

Explorer (chng ta s ch yu s dng mi trng ny!)

khm ph d liu

ExperimenterMi trng cho php tin hnh cc th nghim v thc hin cckim tra thng k (statistical tests) gia cc m hnh hc my

now e ge owMi trng cho php bn tng tc ha kiu ko/th thitk cc bc (cc thnh phn) ca mt th nghim

4Khai Ph DLiu


5/18

WEKA Mi trng Explorer

5Khai Ph DLiu


6/18

WEKA Mi trng Explorer Preprocess

chn v thay i (x l) d liu lm vic Classify

hun luyn v kim tra cc m hnh hc my (phn loi, hochi u /d on

Cluster

hc cc nhm t d liu (phn cm)

khm ph cc lut kt hp t d liu Select attributes

xc nh v la chn cc thuc tnh lin quan (quan trng)nht ca d liu

Visualize

xem (hin th) biu tng tc 2 chiu i vi d liu

6Khai Ph DLiu


7/18

WEKA Khun dng ca tp d liu WEKA chlm vic vi cc tp tin vn bn (text) c khun

dngARFF

V d ca mt tp d liu@r el at i on weat her

Tn ca tpd liu

@at t r i but e out l ook {sunny, over cast , r ai ny}

@at t r i but e t emper at ur e r eal

Thuc tnh

kiu nh danhat t r but e hum d t y r eal

@at t r i but e wi ndy {TRUE, FALSE}

@at t r i but e pl ay {yes, no}

Thuc tnh kiu s

Thuc tnh phn lp

@dat a

sunny, 85, 85, FALSE, no

over cast 83 86 FALSE es

cui cng)

Cc v d

7Khai Ph DLiu


8/18

WEKA Explorer: Tin x l d liu D liu c thc nhp vo (imported) t mt tp tin c

khun d n : ARFF CSV

D liu cng c thc c vo t mt a chURL, hoc tmt c s d liu thng qua JDBC

Cc cng c tin x l d liu ca WEKA c gi l filters

Ri rc ha (Discretization)

Ly mu (Re-sampling)

La chn thuc tnh (Attribute selection)

uy n rans orm ng v p om n ng c c u c n

Hy xem giao din ca WEKA Explorer

8Khai Ph DLiu


9/18

WEKA Explorer: Cc b phn lp (1) Cc b phn lp (Classifiers) ca WEKA tng ng vi

(phn lp) hoc cc i lng kiu s (hi quy/d on)

Nave Bayes classifier and Bayesian networks

Decision trees

Instance-based classifiers

Support vector machines

Neural networks

y xem g ao n c a xp orer

9Khai Ph DLiu


10/18

WEKA Explorer: Cc b phn lp (2) La chn mt b phn lp (classifier)

La chn cc ty chn cho vic kim tra (test options) Use training set. B phn loi hc c sc nh gi

Supplied test set. S dng mt tp d liu khc (vi tp

hc) cho vic nh gi Cross-validation. Tp d liu sc chia u thnh k tp

(folds) c kch thc xp xnhau, v b phn loi hc c sc nh gi bi phng php cross-validation

Percentage split. Chnh t l phn chia tp d liu i vivic nh gi

10Khai Ph DLiu


11/18

WEKA Explorer: Cc b

phn l

p (3) More options

.

Output per-class stats. Hin th cc thng tin thng k vprecision/recall i vi mi lp

.

(entropy) ca tp d liu

Output confusion matrix. Hin th thng tin v ma trn li phn lp(confusion matrix) i vi phn lp hc c

Store predictions for visualization. Cc don ca b phn lpc lu li trong b nh, c thc hin th sau

Output predictions. Hin th chi tit cc don i vi tp kim tra

Cost-sensitive evaluation. Cc li (ca b phn lp) c xc nhda trn ma trn chi ph (cost matrix) chnh

Random seed for XVal / % Split. Chnh gi trrandom seedc sng c o qu r n a c n ng u n n c c v c o p m ra

11Khai Ph DLiu


12/18

WEKA Explorer: Cc b

phn l

p (4) Classifier output hin th cc thng tin quan trng

. ,

d liu, s lng cc v d, cc thuc tnh, v f.f. th nghim Classifier model (full training set). Biu din (dng text) ca

Predictions on test data. Thng tin chi tit v cc don ca

b phn lp i vi tp kim tra ummary. c ng v m c c n x c c a p n p,

i vi f.f. th nghim chn

Detailed Accuracy By Class. Thng tin chi tit v mc chnh

x c c a p n p v m p Confusion Matrix. Cc thnh phn ca ma trn ny th hin s

lng cc v d kim tra (test instances) c phn lp ng vp n p sa

12Khai Ph DLiu


13/18

WEKA Explorer: Cc b

phn l

p (5) Result list cung cp mt s chc nng hu ch

.

c vo trong mt tp tin nh phn (binary file) Load model.c li mt m hnh c hc trc t mt

Re-evaluate model on current test set.nh gi mt m hnh

(b phn lp) hc c trc i vi tp kim tra (test set)n

Visualize classifier errors. Hin th ca s biu th hin cckt qu ca vic phn lp

Cc v dc phn lp chnh xc sc biu din bng k hiubi du cho (x), cn cc v d b phn lp sai sc biu dinbng k hiu vung ()

13Khai Ph DLiu


14/18

WEKA Explorer: Cc b

phn cm (1)

Cc b phn cm (Cluster builders) ca WEKA tng

ti vi mt tp d liu

Expectation maximization (EM)

k-Means ...

Cc b phn cm c thc hin th kt qu v so

s n v c c cm p cHy xem giao din ca WEKA Explorer

14Khai Ph DLiu


15/18

WEKA Explorer: Cc b

phn cm (2)

La chn mt b phn cm (cluster builder)

a c n c p n cm c us er mo e Use training set. Cc cm hc c s c kim tra i vi tp hc

Supplied test set. S dng mt tp d liu khc kim tra cc cmhc c

Percentage split. Ch nh t l phn chia tp d liu ban u cho vic

xy dng tp kim tra u v u . x

hc c i vi cc lp c ch nh

Store clusters for visualization

Lu li cc b phn lp trong b nh, c th hin th sau

Ignore attributes

15Khai Ph DLiu


16/18

WEKA Explorer: Lut k

t h

p

La chn mt m hnh (gii thut) pht hin lut kt hp ssoc a or ou pu

Run information. Cc ty chn i vi m hnh pht hin lutkt hp, tn ca tp d liu, s lng cc v d, cc thuc tnh

Associator model (full training set). Biu din (dng text) catp cc lut kt hp pht hin c

h tr ti thiu (minimum support) tin cy ti thiu (minimum confidence)

Kch thc ca cc tp mc thng xuyn (large/frequentitemsets

Lit k cc lut kt hp tm c


16Khai Ph DLiu


17/18

WEKA Explorer: L

a ch

n thuc tnh

xc nh nhng thuc tnh no l quan trng nht

Trong WEKA, mt phng php la chn thuc tnh(attribute selection) bao gm 2 phn: .

ph hp ca cc thuc tnh

Vd: correlation-based, wrapper, information gain, chi-,

Search Method. xc nh mt phng php (th t) xt ccthuc tnh

Vd: best-first, random, exhaustive, ranking,


17Khai Ph DLiu


18/18

WEKA Explorer: Hin th

d

liu

Hin th d liu rt cn thit trong thc tGip xc nh mc kh khn ca bi ton hc

WEKA c th hin th Mi thuc tnh ring l (1-D visualization) -

Cc gi tr (cc nhn) lp khc nhau sc hin th

bng cc mu khc nhau an r J er r v c n r r ng n,

khi c qu nhiu v d (im) tp trung xung quanh mtv tr trn biu

Tnh nng phng to/thu nh (bng cch tng/gim gi trca PlotSize v PointSize)


18Khai Ph DLiu

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L2-Gioi Thieu WEKA