Assimilate Machine Learning Algorithms in Big Data Analytics: Review

Solanki, Sona D.; Solanki, Asha D.; Borah, Samarjeet

doi:10.1201/9781003337218-5

Cited by 2 publications

(1 citation statement)

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“…Naïve Bayes is a method that is included in a classification algorithm derived from the concept of processing statistical data and probabilities that can predict these opportunities based on previous experience [32], [33].…”

Section: Naïve Bayes Algorithmmentioning

confidence: 99%

Coastal Sentiment Review Using Naïve Bayes with Feature Selection Genetic Algorithm

Somantri¹,

Maharrani²,

Purwaningrum³

2023

SJI

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Purpose: The tourism potential in the maritime sector can be Indonesia's mainstay at this time, especially in enjoying the charm of the natural beauty of the coast as people know Indonesia is an archipelagic country. The purpose of this study is to find the best model by applying the feature selection genetic algorithm (GA) and Information Gain (IG) to get the best Naïve Bayes (NB) model and the best features to produce the best level of sentiment classification accuracy.Methods: The stages of the research were carried out by going through the process of searching, pre-processing, analyzing research data using the Naïve Bayes model and optimizing genetic algorithms, validating data, and model evaluation.Result: The experimental results show that the best model is naïve Bayes based on information gain and the genetic algorithm yields an accuracy rate of 86.34%.Novelty: The main contribution to this research is proposing a new model of the best NB optimization model by applying an optimization algorithm in the search for feature selection to increase sentiment classification accuracy.

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Section: Naïve Bayes Algorithmmentioning

confidence: 99%