Market Basket Analysis & Linear Discriminant Analysis with R
- 4.1
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3.5 hours on-demand video
$
12.99
Brief Introduction
Master: Association rules (MBA) & it's usage, Linear Discriminant Analysis (LDA) for classification & variable selectionDescription
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 rules
- Usage 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 measure
- Confidence measure
- Lift measure
- Basic Algorithm to derive rules
- Demo of Basic Algorithm to derive rules - discussion on breadth first algorithm and depth first algorithm
- Demo Using R - two examples
- Assignment to fortify concepts
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Details of Part 2 - Linear (Market Basket Analysis)
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- Need of a classification model
- Purpose of Linear Discriminant
- A use case for classification
- Formal definition of LDA
- Analytics 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 LDA
- Understand which are three important component to understand LDA properly
- First complexity of LDA - measure distance :Euclidean distance
- First complexity of LDA - measure distance enhanced :Mahalanobis distance
- Second complexity of LDA - Linear Discriminant function
- Third complexity of LDA - posterior probability / Bays theorem
- Demo of LDA using R
- Along with jack knife approach
- Deep dive into LDA outputn
- Visualization of LDA operations
- Understand the LDA chart statistics
- LDA vs PCA side by side
- Demo of LDA for more than two classes: understand
- Data visualization
- Model development
- Model validation on train data set and test data sets
- Industry usage of classification algorithm
- Handling Special Cases in LDA
Requirements
- 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
Gopal Prasad Malakar
4.1 Raiting
Market Basket Analysis & Linear Discriminant Analysis with R
- 4.1
-
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Master: Association rules (MBA) & it's usage, Linear Discriminant Analysis (LDA) for classification & variable selection This course has two parts....
