Illustrate any one classification technique for the data set .Show how we can Classify a new tuple with(Homeowner = yes ; Status =Employed; Income=Average)

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written 8.7 years ago by

teamques10 ★ 69k

• modified 8.7 years ago

Id	Homeowner	Status	Income	Defaulted
1	Yes	Employed	High	No
2	No	Business	Average	No
3	No	Employed	Low	No
4	Yes	Business	High	No
5	No	Unemployed	Average	Yes
6	No	Business	Low	No
7	Yes	Unemployed	High	No
8	No	Employed	Average	Yes
9	No	Business	Low	No
10	No	Employed	Average	Yes

## Illustrate any one classification technique for the above data set .Show how we can Classify a new tuple with(Homeowner = yes ; Status =Employed; Income=Average)

Mumbai University > Information Technology > Sem6 > Data Mining and Business Intelligence

Marks: 10M

Year: May 2015

data mining and business intelligence

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written 8.7 years ago by

teamques10 ★ 69k

P(Yes)=3/10

P(No)=7/10

P(X\Yes) x P(Yes)= $\text{P( yes\yes) x P(Employed\yes)x P(Average\yes) x P(Yes)}\\ =0 * 2/3 * 3/3 * 3/10\\ =0$

P(X\No) x P(No)= $\text{P( yes\no) x P(Employed\no)x P(Average\no) x P(no)} \\ =\text{3/6 * 2/6 * 1/6 * 7/10} \\ =0.0194 \\ =0 \lt0.0194$

Therefore the naive Bayesian classifier predicts Defaulted= “No” …

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278views

written 8.7 years ago by

teamques10 ★ 69k

• modified 8.7 years ago

Homeowner
P(Yes\No )=3/6	P(No\Yes )=3/3	P(Yes\Yes )=0
P(No\No)=4/6
Status
P(Employed \Yes)=2/3	P( Business\Yes)=0	P(Unemployed\Yes) =1/3
P(Employed \No)=2/6	P(Business\No)=4/6	P(Unemployed \No)=1/6
Income
P(High\Yes)=0	P(Low\Yes)=0	P(Average\Yes)=3/3
P(High\No)=3/6	P(Low\No)=3/6	P(Average\No)=1/6

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