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The Key objective here predict the Brain injury occurrences and improvise their prediction so that these instances could be found out as early as possible. Which Algorithm would be best suited would be the Key discussion here. We analyze SVM and KNN here and they both yield their best results according to their potential and the data being involved. Performance analysis, Accuracy prediction, Mean Value Calculation and Standard Deviation are all among their part of the study. The Dataset with 10 instances is the factorable inputs in concern. Predicting the Brain Injury would take a great deal of time and analysis. Predicting one such becomes the need of the hour. Necessary corrective measure will play a major role thereafter, however great measures are taken in order to discover their occurrences and their impact thereafter.

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Efficient Prediction for Outcomes of Brain Injury Using Linear SVM Algorithm in Comparison with Fine KNN Algorithm for Better Accuracy

  • 会议论文

  • 发表日期：

    2025年

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  • G. Sri Lakshmi Sai,
  • Rohith Bhat

摘要

The Key objective here predict the Brain injury occurrences and improvise their prediction so that these instances could be found out as early as possible. Which Algorithm would be best suited would be the Key discussion here. We analyze SVM and KNN here and they both yield their best results according to their potential and the data being involved. Performance analysis, Accuracy prediction, Mean Value Calculation and Standard Deviation are all among their part of the study. The Dataset with 10 instances is the factorable inputs in concern. Predicting the Brain Injury would take a great deal of time and analysis. Predicting one such becomes the need of the hour. Necessary corrective measure will play a major role thereafter, however great measures are taken in order to discover their occurrences and their impact thereafter.