Search Results - (( pattern ((machine algorithm) OR (means algorithm)) ) OR ( centered learning algorithm ))
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Lexicon-based and immune system based learning methods in Twitter sentiment analysis
Published 2016“…Nowadays, there are increasingly numbers of studies on seeking ways to mine Twitter for sentiment analysis. Machine learning approach such as immune system based learning methods is an alternative way for sentiment classification.This method is centered on prominent immunological theory as computation mechanisms that emulate processes in biological immune system in achieving higher probability for pattern recognition. …”
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Conference or Workshop Item -
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Automated Nutritional Guidance for Obesity Management: Insights from Machine Learning, Naïve Bayes, Random Forest
Published 2025“…The system leverages user-specific data, including age, weight, height, activity level, and health goals, to generate tailored dietary plans using machine learning algorithms and nutrition databases. …”
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Frequent Lexicographic Algorithm for Mining Association Rules
Published 2005“…An algorithm called Flex (Frequent lexicographic patterns) has been proposed in obtaining a good performance of searching li-equent patterns. …”
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Image segmentation using an adaptive clustering technique for the detection of acute leukemia blood cells images
Published 2024Subjects:Conference Paper -
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Setting up a new Radiology Center Technology for improvement : Data mining (Image Mining Technique)
Published 2016“…Data mining requires the use of data analysis tool containing statistical model, mathematical algorithms and machine learning methods to determine previously unknown, valid patterns and relationships in huge volume data. …”
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Monograph -
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An efficient fuzzy C-least median clustering algorithm
Published 2021“…In this paper we are discussing our new procedure for clustering called Fuzzy C-least median of squares algorithm which is an improvement to Fuzzy C-means (FCM) algorithm. …”
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Predicting building damage grade by earthquake: a Bayesian Optimization-based comparative study of machine learning algorithms
Published 2024“…Bayesian Optimization optimizes machine learning algorithm hyperparameters to solve this problem. …”
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Characterization of water quality conditions in the Klang River Basin, Malaysia using self organizing map and K-means algorithm
Published 2015“…The self organizing map (SOM) combined with the K-means algorithm arranged the data based on the relationships of 25 variables. …”
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Music Recommender System Using Machine Learning Content-Based Filtering Technique
Published 2022“…These algorithms identify hidden patterns or data groupings without the assistance of a human. …”
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Undergraduates Project Papers -
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Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model
Published 2018“…EM and K-means clustering algorithms are used to cluster the multi-class classification attribute according to its relevance criteria and afterward, the clustered attributes are classified using an ensemble random forest classifier model. …”
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Social media mining: a genetic based multiobjective clustering approach to topic modelling
Published 2021“…Although effective, the performance of the k-means clustering algorithm depends heavily on the initial centroids and the number of clusters, k. …”
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Modeling, Testing and Experimental Validation of Laser Machining Micro Quality Response by Artificial Neural Network
Published 2009“…Therefore, prediction of laser machining cut quality, namely surface roughness was carried out using machine learning techniques based on Quick Back Propagation Algorithm using ANN. …”
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River flow prediction based on improved machine learning method: Cuckoo Search-Artificial Neural Network
Published 2024“…Therefore, it is necessary to precisely estimate how the river flow will alter as a result of changing rainfall patterns. Finding the best value for the hyper-parameters is one of the problems with machine learning algorithms, which have lately been adopted by many academics. …”
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Partitional clustering algorithms for highly similar and sparseness y-short tandem repeat data / Ali Seman
Published 2013“…Out of six data sets, the &-AMH algorithm obtained the highest mean accuracy scores for the five data sets and one data set was at equal performance. …”
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A Hybrid Rough Sets K-Means Vector Quantization Model For Neural Networks Based Arabic Speech Recognition
Published 2002“…A vector quantization model that incorporate rough sets attribute reduction and rules generation with a modified version of the K-means clustering algorithm was developed, implemented and tested as a part of a speech recognition framework, in which the Learning Vector Quantization (LVQ) neural network model was used in the pattern matching stage. …”
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Ensemble Classifier for Recognition of Small Variation in X-Bar Control Chart Patterns
Published 2023“…This study provides an improved control chart pattern recognition (CCPR) method focusing on X-bar chart patterns of small process variations using an ensemble classifier comprised of five complementing algorithms: decision tree, artificial neural network, linear support vector machine, Gaussian support vector machine, and k-nearest neighbours. …”
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Social media mining: a genetic based multiobjective clustering approach to topic modelling
Published 2021“…Although effective, the performance of the k-means clustering algorithm depends heavily on the initial centroids and the number of clusters, k. …”
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