Search Results - (((( patterns using algorithm ) OR ( pattern means algorithm ))) OR ( peer learning algorithm ))
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1
Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition
Published 2017“…Phase 1 is mainly to evaluate the performance of clustering algorithm (K-Means and FCM). Phase 2 is to study the performance of proposed integration system which using the data clustered to be used as train data for Naïve Bayes classifier. …”
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2
Clustering ensemble learning method based on incremental genetic algorithms
Published 2012“…In the first and second phases, a threshold fuzzy c-means clustering algorithm as a clusterer and a pattern ensemble learning method based on the incremental genetic-based algorithms are proposed respectively. …”
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3
Frequent Lexicographic Algorithm for Mining Association Rules
Published 2005“…The primary concept of association rule algorithms consist of two phase procedure. In the first phase, all frequent patterns are found and the second phase uses these frequent patterns in order to generate all strong rules. …”
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4
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“…The best mapping percentage of 62.7 obtained using the proposed algorithm when k = 15 is obtained to outperform the performance of the generic k-means. …”
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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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7
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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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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The effect of adaptive parameters on the performance of back propagation
Published 2012“…The Back Propagation algorithm or its variation on Multilayered Feedforward Networks is widely used in many applications. …”
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10
Development of an intelligent system using Kernel-based learning methods for predicting oil-palm yield.
Published 2005“…The proposed algorithm can effectively handle noise, outliers and auto-correlation in the spatial data, for effective and efficient data analysis by exploring patterns and structures in the data, and thus can be used for predicting oil-palm yield by analyzing various factors affecting oil-palm yield.…”
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Social media mining: a genetic based multiobjective clustering approach to topic modelling
Published 2021“…The best mapping percentage of 62.7 obtained using the proposed algorithm when k = 15 is obtained to outperform the performance of the generic k-means. …”
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Simulation model algorithm for pre-hospital emergency care (PHEC) volunteers in Indonesia
Published 2018“…The statistic test used in this research is t-test. The results reveals that simulation model using algorithm influences the improvement of traffic volunteers’ emergency management capabilities with p-value of < 0.05 and mean score difference of 34.5%, and the model is highly effective to be implemented to improve the capability of traffic assistant volunteers to manage trauma emergency with the mean score difference of 11.5%. …”
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Partitional clustering algorithms for highly similar and sparseness y-short tandem repeat data / Ali Seman
Published 2013“…Six Y-STR data sets were used as a benchmark to evaluate the performances of the algorithm against the other eight partitional clustering algorithms. …”
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14
Clustering Student Performance Data Using k-Means Algorithms
Published 2023“…Clustering, an unsupervised learning technique, is one of the most powerful machine- learning tools for discovering patterns and unseen data. This work aims to provide insights into the data obtained from Oman Education Portal (OEP) related to the student’s performance by manipulating the k-means algorithm.…”
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Predicting building damage grade by earthquake: a Bayesian Optimization-based comparative study of machine learning algorithms
Published 2024“…This study compares Bayesian Optimization-based machine learning systems that anticipate earthquake-damaged buildings and to evaluates building damage classification models. Using metrics, this study evaluates Random Forest, ElasticNet, and Decision Tree algorithms. …”
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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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Cabbage disease detection system using k-NN algorithm
Published 2022“…Finally, the KNN algorithm will be used to classify the disease based on sample nature and a cabbage disease data set. …”
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Academic Exercise -
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A framework for predicting oil-palm yield from climate data
Published 2006“…The proposed algorithm can effectively handle noise, outliers and auto-correlation in the spatial data, for effective and efficient data analysis by exploring patterns and structures in the data, and thus can be used for predicting oil-palm yield by analyzing various factors affecting the yield.…”
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Conference or Workshop Item -
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