Skip to main content

NAIVE BAYES CATEGORICALNB CLASSIFICATION


DA2 ML (3RD AND 4TH)QUESTION


Binary, Code, Privacy Policy, Brain, View, Profile

QUESTIONS:

 

A

B

C

D

Output

Some

High

False

French

Yes

Full

Low

False

Thai

No

Some

Low

False

Burger

Yes

Full

Low

False

Thai

Yes

Full

High

False

French

No

Some

Normal

True

Italian

Yes

None

Low

True

Burger

No

Some

Normal

True

Thai

Yes

Full

Low

True

Burger

No

Full

High

False

Italian

No

None

Low

False

Thai

Yes

Full

Low

False

Burger

Yes


1.      Using Bayes classifier, identify the output when the values are given as (A = Full, B = Normal,  C=False, D=Thai).

2.      Using Baye’s classifier, predict the output for all input instances used for training and analyze the metrics.

Popular posts from this blog

IMPLEMENTATION OF KNN CLASSIFIER

1.       Predict the food type for tomato (A = 6 B = 4) with k=2 using the below the training data set.   Ingredient A B Food Type Grape 8 5 Fruit Beans 3 7

KNN CLASSIFIER

DA2 ML VITOL PART3   A B C D Output Some High False French Yes Full Low False Thai No Some

Example problem on simple linear regression

1.      Consider the following farmer dataset.   Number of pounds per acre (in hundreds) Bushels per acre X y 1.0 25 2.5 32 3.0 35 3.0 32 3.4