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Optimal Feature Selection for Big Data Classification: Firefly with Lion-Assisted Model.

Ramar Senthamil Selvi1, Muniyappan Lakshapalam Valarmathi2

  • 1Saranathan College of Engineering, Tiruchirappalli, India.

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|April 23, 2020
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Summary
This summary is machine-generated.

This study introduces a big data classification model using intelligent techniques and the Lion-based Firefly (L-FF) algorithm for optimal feature selection, achieving superior performance with neural networks (NN). The L-FF+NN model enhances big data analysis accuracy and efficiency.

Keywords:
Lion with Firefly algorithmbig data classificationfeature classificationoptimal feature selectionperformance measures

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Area of Science:

  • Computer Science
  • Artificial Intelligence
  • Data Science

Background:

  • Big data classification presents challenges due to high-dimensional feature vectors.
  • Existing methods struggle with optimal feature selection, impacting classification accuracy.
  • Intelligent techniques offer potential for improved big data analysis.

Purpose of the Study:

  • To develop an efficient big data classification model.
  • To enhance feature selection using an intelligent algorithm.
  • To improve classification accuracy through optimal feature subsets.

Main Methods:

  • Utilized the Parallel Pool MapReduce Framework for big data processing.
  • Employed Principle Component Analysis, Linear Discriminant Analysis, and Linear Square Regression for feature extraction.
  • Implemented the Lion-based Firefly (L-FF) algorithm for optimal feature selection, minimizing feature correlation.
  • Adopted a neural network (NN) classifier for data classification using selected features.

Main Results:

  • The proposed L-FF+NN model demonstrated significant superiority over traditional methods.
  • Achieved performance improvements of 92% over GA+NN, 28% over FF+NN, 87% over PSO+NN, 82% over ABC+NN, and 78% over LA+NN.
  • The L-FF algorithm effectively reduced feature vector length and correlation, enhancing classification.

Conclusions:

  • The L-FF+NN model provides an effective approach for big data classification.
  • Intelligent feature selection significantly boosts classification performance.
  • The method offers a robust solution for handling and classifying large datasets.