A comparative analysis of K-Nearest Neighbor, Genetic, Support Vector Machine, Decision Tree, and Long Short Term Memory algorithms in machine learning

Machine learning (ML) is a new-age thriving technology, which facilitates computers to read and interpret from the previously present data automatically. The paper answers all relevant questions that may arise during the study of these algorithms ranging from their origin, to their definition, methodologies of execution, real-time applications attached with sufficient novel evidence, followed by the advantages and major trade-offs; lastly an elaborate comparison of their performances on quantita...

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• 1 It makes use of multiple algorithms to build models, mathematical in nature, and then makes predictions for the new data using the past data and knowledge.
• 2 Lately, it has been adopted for text detection, hate speech detection, recommender system, face detection, and more.
• 3 In this paper, majorly all the aspects concerning five machine learning algorithms namely-K-Nearest Neighbor (KNN), Genetic Algorithm (GA), Support Vector Machine (SVM), Decision Tree (DT) , and Long Short Term Memory (LSTM) network have been discussed in great detail which is a prerequisite for venturing into the field of ML.

This research advances how AI systems learn, reason, and solve problems — with direct implications for automation and scientific discovery.

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