Search Results - (( pattern machine algorithm ) OR ( patterns ((ant algorithm) OR (bayes algorithm)) ))*
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Incremental continuous ant colony optimization for tuning support vector machine’s parameters
Published 2013“…Support Vector Machines are considered to be excellent patterns classification techniques. …”
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Optimizing support vector machine parameters using continuous ant colony optimization
Published 2012“…Support Vector Machines are considered to be excellent patterns classification techniques.The process of classifying a pattern with high classification accuracy counts mainly on tuning Support Vector Machine parameters which are the generalization error parameter and the kernel function parameter.Tuning these parameters is a complex process and may be done experimentally through time consuming human experience.To overcome this difficulty, an approach such as Ant Colony Optimization can tune Support Vector Machine parameters.Ant Colony Optimization originally deals with discrete optimization problems. …”
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Naive Bayes-guided bat algorithm for feature selection
Published 2023Subjects: “…Algorithms…”
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Machine Learning Applications in Offense Type and Incidence Prediction
Published 2024“…We can develop targeted strategies to prevent and respond to such incidents by analyzing these patterns. Artificial Intelligence (AI) techniques encompass variouscomputational methods and algorithms designed to enable machines to perform tasks that typically require human intelligence. …”
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Hybrid ACO and SVM algorithm for pattern classification
Published 2013“…Ant Colony Optimization (ACO) is a metaheuristic algorithm that can be used to solve a variety of combinatorial optimization problems. …”
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Naive bayes-guided bat algorithm for feature selection.
Published 2013“…Bio-inspired method called Bat Algorithm hybridized with a Naive Bayes classifier has been presented in this work. …”
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Predicting hearing loss symptoms from Audiometry data using FP-Growth Algorithm and Bayesian Classifier
Published 2013“…The effect of extracting naïve Bayes classifier’s vocabulary from patterns generated by FP-Growth algorithm was explored. …”
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The analysis of road traffic fatality pattern for Selangor, Malaysia case study
Published 2021“…The analysed algorithms among others are neural network, random forest, decision tree, logistic regression, naïve Bayes, and support vector machine. …”
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Ant system-based feature set partitioning algorithm for classifier ensemble construction
Published 2016“…All of these approaches attempt to generate diversity in the ensemble.However, classifier ensemble construction still remains a problem because there is no standard guideline in constructing a set of accurate and diverse classifiers. In this study, Ant system-based feature set partitioning algorithm for classifier ensemble construction is proposed.The Ant System Algorithm is used to form an optimal feature set partition of the original training set which represents the number of classifiers.Experiments were carried out to construct several homogeneous classifier ensembles using nearest mean classifier, naive Bayes classifier, k-nearest neighbor and linear discriminant analysis as base classifier and majority voting technique as combiner. …”
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Traditional marble game using ant colony optimization / Muhammad Izzat Imran Che Isa
Published 2017“…In future, traditional marble game can be applied with other search algorithm to optimize the solution…”
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Evaluation of fall detection classification approaches
Published 2012“…The algorithms are Multilayer Perceptron, Naive Bayes, Decision tree, Support Vector Machine, ZeroR and OneR. …”
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Comparative study of machine learning algorithms in data classification
Published 2025“…This research conducts a comparative study of various machine learning algorithms for dataset classification to identify the most accurate and reliable classifier. …”
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Employability prediction based on personality test using Naive Bayes Algorithm / Mohd Alief Mukhlis Mohd Adnin
Published 2020“…The purpose of this project was to identify the personality type of person that can be used for employability prediction, to design a prototype model of prediction using Naive Bayes algorithm and to test the functionality the proposed prototype. …”
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A behavioral trust model for internet of healthcare things using an improved FP-growth algorithm and Naïve Bayes classifier
Published 2021“…Towards securing these frameworks through an intelligent TMM, this work proposes a machine learning based Behavioral Trust Model (BTM), where an improved Frequent Pattern Growth (iFP-Growth) algorithm is proposed and applied to extract behavioral signatures of various trust classes. …”
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Identification model for hearing loss symptoms using machine learning techniques
Published 2014“…The model is implemented using both unsupervised and supervised machine learning techniques in the form of Frequent Pattern Growth (FP-Growth) algorithm as feature transformation method and multivariate Bernoulli naïve Bayes classification model as the classifier. …”
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Lexicon-based and immune system based learning methods in Twitter sentiment analysis
Published 2016“…In future work, the accuracy of proposed model can be strengthened by comparative study with other heuristic based searching algorithms such as genetic algorithm, ant colony optimization, swam algorithms and etc.…”
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Prediction of stroke disease using machine learning techniques / Syarifah Adilah Mohamed Yusoff ... [et al.]
Published 2024“…This study has investigated five commonly used machine learning algorithm to be constructed as potential models for predicting stroke dataset. …”
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Mobile app of mood prediction based on menstrual cycle using machine learning algorithm / Nur Hazirah Amir
Published 2019“…It implemented Supervised Learning algorithm with Bayes’ Theorem model for the calculation of mood prediction using Python programming language. …”
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Investigating optimal smartphone placement for identifying stairs movement using machine learning
Published 2023“…The data was trained against 6 machine learning algorithms namely Decision Tree, Logistic Regression, Naive Bayes, Random Forest, Neural Networks and KNN. …”
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