Lab 11: Naive Bayes Classification Lab Instructions: Naive Bayes Classification Primer • You're not allowed to use external libraries for this lab. • This is an individual Lab assignment. Each student must submit their own work. Tasks: • Apply Naive Bayes Classification on the attached dataset_sunny.csv and determine the probability of Play given a certain feature vector. • What is the probability of playing golf given a feature vector You should implement at least one function called a classifier that takes in a feature vector as a list and outputs a tuple with probability for a yes and a no i.e. classifier([“sunny", “hot", “high", False]) => (0.67, 0.33)

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
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PYTHON PROGRAMMING TASK. PLEASE DONT:USE ANY EXTERNAL LIBRARIES. DO NOT USE SKLEARN. ONLY use math lib and csv as libraries. WRITE NAIVES BAYES CLASSIFIER FROM SCRATCH: 

Lab 11: Naive Bayes Classification
Lab Instructions:
Naive Bayes Classification Primer
• You're not allowed to use external libraries for this lab.
• This is an individual Lab assignment. Each student must submit their own work.
Tasks:
• Apply Naive Bayes Classification on the attached dataset_sunny.csv and
determine the probability of Play given a certain feature vector.
• What is the probability of playing golf given a feature vector <sunny, hot, normal,
False>
• You should implement at least one function called a classifier that takes in a
feature vector as a list and outputs a tuple with probability for a yes and a no i.e.
classifier([“sunny", “hot", "high", False]) => (0.67, 0.33)
Transcribed Image Text:Lab 11: Naive Bayes Classification Lab Instructions: Naive Bayes Classification Primer • You're not allowed to use external libraries for this lab. • This is an individual Lab assignment. Each student must submit their own work. Tasks: • Apply Naive Bayes Classification on the attached dataset_sunny.csv and determine the probability of Play given a certain feature vector. • What is the probability of playing golf given a feature vector <sunny, hot, normal, False> • You should implement at least one function called a classifier that takes in a feature vector as a list and outputs a tuple with probability for a yes and a no i.e. classifier([“sunny", “hot", "high", False]) => (0.67, 0.33)
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