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Feature Engineering

  • July 15, 2023
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Meet the Author : Mr. Bharani Kumar

Bharani Kumar Depuru is a well known IT personality from Hyderabad. He is the Founder and Director of Innodatatics Pvt Ltd and 360DigiTMG. Bharani Kumar is an IIT and ISB alumni with more than 18+ years of experience, he held prominent positions in the IT elites like HSBC, ITC Infotech, Infosys, and Deloitte. He is a prevalent IT consultant specializing in Industrial Revolution 4.0 implementation, Data Analytics practice setup, Artificial Intelligence, Big Data Analytics, Industrial IoT, Business Intelligence and Business Management. Bharani Kumar is also the chief trainer at 360DigiTMG with more than Ten years of experience and has been making the IT transition journey easy for his students. 360DigiTMG is at the forefront of delivering quality education, thereby bridging the gap between academia and industry.

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Feature Extraction and Feature Engineering are other names for attribute generation. Try to use domain expertise to create more insightful derived variables from the provided variables.

Feature Extraction can be performed on:

  • For Temporal Data
    • Date Based Features
    • Time-Based Features
  • For Numeric Data
  • For Categorical Data
  • On Text Data
  • On Image Data
feature extraction

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Feature Extraction

  • Deep Learning is performed using Automatic Extraction
  • Shallow Machine Learning is performed using Manual Extraction
  • Feature Extraction is used to get either Derived Features or Normalized Features

Feature Selection

Shortlisting a subset of characteristics or attributes is known as feature selection or attribute selection.

It is based on:

  • Attribute importance
  • Quality
  • Relevancy
  • Assumptions
  • Constraints
feature extraction

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Filter Methods

  • Wrapper Methods
  • Embedded Methods
  • Threshold-Based Methods
  • Statistical Methods
  • Hypothesis Testing
  • Recursive Feature Elimination
  • Model-Based Selection
  • Information Gain
  • Variable Importance Plot
  • Subset Selection Methods includes:
    • Best Subset Selection (Lasso Regression, Ridge Regression)
    • Forward Stepwise Selection
    • Backward Stepwise Selection

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