0000015157 05 Classification Algoritma Decision Tree

(1)

CLASSIFICATION

Algoritma Decision Tree

(2)

K

EY

P

ROBLEM

No

Savings

Assets

Income

Credit

Risk

1 Medium

High

Good

2 Low

Low

Medium

Bad

3 High

Medium

Low

Bad

4 Medium

Medium

Good

5 Low

Medium

High

Good

6 High

High

Low

Good

7 Low

Low

Bad

8 Medium

Medium

Good

Savings

Assets

Income

Credit Risk

Medium

Low

Medium

?

(3)

M

ENGHITUNG

I

MPURITY

Menghit ung Kesam aan dat a ( hom ogeneit y) at au ket idaksam aan dat a ( het erogeneit y) dalam sebuah t abel yang m engandung at ribut dan Kelas dari at ribut .

Sebuah t abel dikat akan Pure at au Hom ogenous j ika hanya m engandung sat u class. Jika m engandung lebih dari sat u kelas disebut I m pure at au Het erogeneous.

(4)

P

ROBABILITY

Atribut

Class

No

Savings

Assets

Income

Credit Risk

1 Medium

High

Good

2 Low

Low

Medium

Bad

3 High

Medium

Low

Bad

4 Medium

Medium

Good

5 Low

Medium

High

Good

6 High

High

Low

Good

7 Low

Low

Bad

8 Medium

Medium

Good

Terdapat 3 Class Bad dan 5 Class Good. Total data 8 baris.

Probabilit y Class adalah :

(5)

E

NTROPY

P

ARENT

Ent ropy Parent = – 0.375 log ( 0.375) – 0.625 log ( 0.625) = – 0.375 ( – 0.426) – 0.625 ( – 0.205) = 0.15975 + 0.12815

= 0.29 Probabilit y Class adalah :

(6)

G

INI

I

NDEX

Gini I ndex = 1 – ( 0.3752 _{+ 0.625}2₎

= 1 – ( 0.14 + 0.39) = 1 – 0.53

(7)

C

LASSIFICATION

E

RROR

I

NDEX

Classificat ion Error I ndex = 1 – Max{ 0.375, 0.625} = 1 - 0.625

(8)

(9)

S

UBSET

- S

AVINGS

Atribut Class

No Savings Credit Risk

1 Low Bad

2 Low Bad

3 Low Good

4 Medium Good

5 Medium Good

6 Medium Good

(10)

S

UBSET

- A

SSETS

Atribut Class

No Assets Credit Risk

1 Low Bad

2 Low Bad

3 Medium Bad

4 Medium Good

5 Medium Good

6 Medium Good

(11)

S

UBSET

- I

NCOME

No Income Credit Risk

1 Low Bad

2 Low Bad

3 Low Good

7 High Good

8 High Good

(12)

I

NFORMATION

G

AIN

I nform at ion Gain ( i) Ent ropy :

Ent ropy dari Parent Tabel D – Sum ( ( Jum lah Dat a Subset / Jum lah

Dat a Parent ) * Ent ropy set iap Subset )

I nform at ion Gain ( i) Gini I ndex :

Gini I ndex dari Parent Tabel D – Sum ( ( Jum lah Dat a Subset / Jum lah

Dat a Parent ) * Gini I ndex set iap Subset )

I nform at ion Gain ( i) Classificat ion Error :

Classificat ion Error dari Parent Tabel D – Sum ( ( Jum lah Dat a

(13)

I

NFORMATION

G

AIN

Savings Assets Income

Gini Index

Low (3) 0.46 Low (2) 0 Low (3) 0.46

Medium (3) 0 Medium (4) 0.375 Medium (3) 0.46

High (2) 0.5 High (2) 0 High (2) 0

Maxim um I nform at ion Gain = Subset Asset s Pure ( Hom ogen) Subset Asset s = Low dan High

Assets

Low

High Medium

Bad

(14)

D

ECISION

T

REE

R

ULE

Assets

Low

High Medium

Bad

Good

?

(15)

P

ARENT

- I

TERATION

#2

No Assets Savings Income Credit Risk

1 Medium High Low Bad

2 Medium Medium Medium Good

3 Medium Medium Medium Good

4 Medium Low High Good

Prob ( Bad) : 1/ 4 = 0.25 Prob ( Good) : 3/ 4 = 0.75

Gini I ndex : 1 – ( 0.252 _{+ 0.75}2₎

(16)

S

UBSET

S

AVINGS

- #2

1 High Bad

2 Medium Good

3 Medium Good

4 Low Good

1 High Bad

1 Medium Good

2 Medium Good

(17)

S

UBSET

I

NCOME

- #2

1 Low Bad

2 Medium Good

3 Medium Good

4 High Good

1 Low Bad

1 High Good

(18)

I

NFORMATION

G

AIN

- #2

Maxim um I nform at ion Gain = Subset Savings dan Subset I ncom e Pure ( Hom ogen) Subset Savings = Low, Medium dan High

(19)

(20)

(21)

D

ECISION

T

REE

R

ULE

- R

ESULT

# 1. I f Asset s = Low Then Credit Risk = Bad # 2. I f Asset s = High Then Credit Risk = Good

# 3a. I f Asset s = Medium And Savings = Low Then Credit Risk = Good # 4a. I f Asset s = Medium And Savings = High Then Credit Risk = Bad

# 5a. I f Asset s = Medium And Savings = Medium Then Credit Risk = Good

# 3b. I f Asset s = Medium And I ncom e = Low Then Credit Risk = Bad # 4b. I f Asset s = Medium And I ncom e = High Then Credit Risk = Good # 5b. I f Asset s = Medium And I ncom e = Medium Then Credit Risk = Good