Question 1:1.1: How can we convert a continuous feature into a categorical feature using binning? (Read and summarize the part of the chapter related to Naïve Bayes classification in the book) Question 2:The table below lists a dataset that we want to use to predict whether it will be good day for a picnic.TPClassS11S21M11L21S11M21M32L22M12L22L32L22 Can we cast the prediction as a binary classification task. Explain your answer.We consider applying Naïve Bayes classifier. Provide the results of the training phase.Given the query Q=[ T ="L", P="1"], what would the Naïve Bayes classifier prediction be? Explain your answer. Question 1:1.1: How can we convert a continuous feature into a categorical feature using binning?(Read and summarize the part of the chapter related to Naïve Bayes classification in thebook)Question 2:The table below lists a dataset that we want to use to predict whether it will be good dayfor a picnic.PClass11S21M11L211M2M322M122L32221. Can we cast the prediction as a binary classification task. Explain your answer.2. We consider applying Naïve Bayes classifier. Provide the results of the training phase.3. Given the query Q=[ T ="L", P="1"], what would the Naïve Bayes classifier prediction be? Explainyour answer.

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Database System Concepts

7th Edition

ISBN:9780078022159

Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Chapter1: Introduction

Section: Chapter Questions

Problem 1PE

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Question

Question 1:

1.1: How can we convert a continuous feature into a categorical feature using binning? (Read and summarize the part of the chapter related to Naïve Bayes classification in the book)

Question 2:

The table below lists a dataset that we want to use to predict whether it will be good day for a picnic.

T	P	Class
S	1	1
S	2	1
M	1	1
L	2	1
S	1	1
M	2	1
M	3	2
L	2	2
M	1	2
L	2	2
L	3	2
L	2	2

Can we cast the prediction as a binary classification task. Explain your answer.
We consider applying Naïve Bayes classifier. Provide the results of the training phase.
Given the query Q=[ T ="L", P="1"], what would the Naïve Bayes classifier prediction be? Explain your answer.

Question 1:
1.1: How can we convert a continuous feature into a categorical feature using binning?
(Read and summarize the part of the chapter related to Naïve Bayes classification in the
book)
Question 2:
The table below lists a dataset that we want to use to predict whether it will be good day
for a picnic.
P
Class
1
1
S
2
1
M
1
1
L
2
1
1
M
2
M
3
2
2
M
1
2
2
L
3
2
2
2
1. Can we cast the prediction as a binary classification task. Explain your answer.
2. We consider applying Naïve Bayes classifier. Provide the results of the training phase.
3. Given the query Q=[ T ="L", P="1"], what would the Naïve Bayes classifier prediction be? Explain
your answer.

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