Titlebook: Smart Data Intelligence; Proceedings of ICSMD R. Asokan,Diego P. Ruiz,Selwyn Piramuthu Conference proceedings 2024 The Editor(s) (if applic

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Implementation of Machine Learning Algorithms in Diabetes Prediction,orithm produces varying results when compared to the others. However, when comparing these outcomes, it is evident that the K-nearest neighbor with grid search optimization techniques and support vector machine yield the most accurate results. Both algorithms achieve a remarkable accuracy rate of 99

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Identification and Prevention of Brute Force Attacks,indications that the system or its networks are being tampered with, passive attacks are difficult to identify. This study utilizes the decision tree algorithm to identify brute force attacks against Linux systems from the data logs using Python coding. Additionally, prevention and protection strate

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Fairness in Predicting Recidivism Score,rithm. ProPublica, p 9, 2016 [2]), collected by ProPublica and obtained via Kaggle, is used. Several models are used to train the dataset and compare how this model find the hidden patterns and reduce bias in predicting, and they are support vector machine (SVM), decision tree, and ensemble learning

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,System Analysis of Adaptive Genetic Algorithms for Water Dıstribution Optimizing in Water Scarcity of restrictions, are considered. Various modifications of GA are considered and systemically generalized, including dynamic algorithms characterized by a change in the population volume during the search, as well as hybrid algorithms based on Lamarck evolution modeling and various types of adaptive

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S. Parvathavarthini,S. Sengottayan,U. M. Arun,U. Bhuvaneshwaran

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