The figure below is a graph I happened to see from a weblog on machine learning. This graph is supposed to illustrate logistic regression with binary responses. However, it is an incorrect representation of logistic regression. Explain what is the mistake and sketch a correct plot.

The figure below is a graph I happened to see from a weblog on machine learning. This graph is supposed to illustrate logistic regression with binary responses. However, it is an incorrect representation of logistic regression. Explain what is the mistake and sketch a correct plot.

Functions and Change: A Modeling Approach to College Algebra (MindTap Course List)

6th Edition

ISBN:9781337111348

Author:Bruce Crauder, Benny Evans, Alan Noell

Publisher:Bruce Crauder, Benny Evans, Alan Noell

Chapter5: A Survey Of Other Common Functions

Section5.1: Logistic Functions

Problem 17E: World Population The following table shows world population N, in billions, in the given year. Year...

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Concept explainers

Correlation

Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.

Linear Correlation

A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.

Regression Analysis

Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.

Question

The figure below is a graph I happened to see from a weblog on machine learning.
This graph is supposed to illustrate logistic regression with binary responses. However, it is
an incorrect representation of logistic regression. Explain what is the mistake and sketch a
correct plot.
Logistic Regression Example
0.9
0.8
0.7
0.6
y as
Boundary
False samples
• True samples
0.4
0.2
0.1
0.2
0.4
0.6
0.8
X

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