Market Basket Analysis & Linear Discriminant Analysis With R

Master: Association rules (MBA) & it's usage, Linear Discriminant Analysis (LDA) for classification & variable selection

What you'll learn
Students will know what is association rules (Market Basket Analysis)?
How do association rules work?
How to do market basket analysis using Excel & R
What is linear discriminant analysis?
How to do linear discriminant analysis using R?
How to understand each component of the linear discriminant analysis output?
Practical usage of linear discriminant analysis

Requirements
Basic understanding of R and R studio
Basic understanding of statistics as the course will assume knowledge of linear regression, variance etc.
Basic fmiliarity with udemy platform - user should know how to download files etc

Description
This course has two parts. In part 1 Association rules (Market Basket Analysis) is explained. In Part 2, Linear Discriminant Analysis (LDA) is explained. L
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Details of Part 1 - Association Rules / Market Basket Analysis (MBA)
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What is Market Basket Analysis (MBA) or Association rulesUsage of Association Rules - How it can be applied in a variety of situations How does an association rule look like?Strength of an association rule - Support measureConfidence measure Lift measureBasic Algorithm to derive rulesDemo of Basic Algorithm to derive rules - discussion on breadth first algorithm and depth first algorithmDemo Using R - two examplesAssignment to fortify concepts
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Details of Part 2 - Linear  (Market Basket Analysis)
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Need of a classification modelPurpose of Linear DiscriminantA use case for classificationFormal definition of LDAAnalytics techniques applicability Two usage of LDA LDA for Variable Selection Demo of using LDA for Variable Selection Second usage of LDA - LDA for classification
Details on second practical usage of LDAUnderstand which are three important component to understand LDA properlyFirst complexity of LDA - measure distance :Euclidean distance First complexity of LDA - measure distance enhanced  :Mahalanobis distanceSecond complexity of LDA - Linear Discriminant functionThird complexity of LDA - posterior probability / Bays theorem
Demo of LDA using RAlong with jack knife approachDeep dive into LDA outputnVisualization of LDA operationsUnderstand the LDA chart statistics
LDA vs PCA side by sideDemo of LDA for more than two classes: understandData visualizationModel developmentModel validation on train data set and test data setsIndustry usage of classification algorithm Handling Special Cases in LDA

Who this course is for:
Market Research Professionals,Business Analytics professionals,Data Scientists