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Multiple choice questions Question: Which of the following statements about Logistic Regression is NOT true? A)The algorithm can handle categorical variables directly. So, we don't need to convert

Multiple choice questions Question: Which of the following statements about Logistic Regression is NOT true? A)The algorithm can handle categorical variables directly. So, we don't need to convert

Database System Concepts
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
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Multiple choice questions Question: Which of the following statements about Logistic Regression is NOT true? A)The algorithm can handle categorical variables directly. So, we don't need to convert the categorical data into a numerical format that is suitable for the algorithm to process B)It's a classification algorithm that is used where the target feature is of categorical nature C) The main objective behind Logistic Regression is to determine the relationship between features and the probability of a particular outcome D) The decision boundary is line or a plane that separates the target features into different clauses that can be either linear or nonlinear E)In multinomial logistic regressionthe target variable can have three or more possible values without any order.
Transcribed Image Text:Multiple choice questions Question: Which of the following statements about Logistic Regression is NOT true? A)The algorithm can handle categorical variables directly. So, we don't need to convert the categorical data into a numerical format that is suitable for the algorithm to process B)It's a classification algorithm that is used where the target feature is of categorical nature C) The main objective behind Logistic Regression is to determine the relationship between features and the probability of a particular outcome D) The decision boundary is line or a plane that separates the target features into different clauses that can be either linear or nonlinear E)In multinomial logistic regressionthe target variable can have three or more possible values without any order.
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