What is the Multinomial-Logistic Regression Classification Algorith...

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Master the Art of Analytics
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Multinomial Logistic
Regression

Terminologies
Introduction & Example
Standard input/tuning parameters & Sample UI
Sample output UI
Interpretation of Outpu...

Terminologies

Terminologies
 Target variable usually denoted by Y , is the variable being predicted and is also
called dependent variab...

Introduction & Example

Introduction
• OBJECTIVE :
• Logistic regression measures the relationship
between the categorical target variable and one...

Example : Multinomial Logistic Regression :
Input Let’s conduct the Multinomial Logistic Regression analysis on following ...

Example : Multinomial Logistic Regression :
Output 1 Coefficient P value
High
Age 1.54 0.05
Income -0.34 0.03
Male 0.67 0....

Example : Multinomial Logistic Regression :
Output 2
Classification Accuracy : (50+ 10 + 70) / (50+ 10 + 70+ 4+4+5+4+6+7) ...

Standard input/tuning
parameters & Sample
UI

STANDARD
INPUT
PARAMETERS
& SAMPLE UI

SAMPLE OUTPUT UI

Sample output 1 : Model Summary
Actual versus predicted
Predicted
Actual
Coefficient matrix :
Low Medium High
Low 50 4 4
M...

Age Marital Status Gender Income
Job satisfaction
level
Predicted
class
Probability
58 married Female 46,399 Low Low 0.7
4...

Sample Output 3 : Classification Plot
• Lesser the overlap among three classes in the plot above , better the classificati...

Interpretation of
Output

Interpretation of Important Model Summary
Statistics
Accuracy:
 If Accuracy >= 70% : Model is well fit on
provided data a...

Limitations

Limitations
 It is applicable only when target variable is categorical
 Sample size must be at least 1000 in order to ge...

Business Use Cases

Use case 1
Business benefit:
• By having a knowledge of probable
election outcome, proper strategy
can be put in place in ...

Use case 1 : Sample Input Dataset
Responder
ID
Qualification income Age Gender Occupation
Done voting in
past
Preferred pa...

Use case 1 : Output : Predicted Class
Output : Each record will have a predicted class along with probability assigned as
...

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