Search Results - (( java application learning algorithm ) OR ( using data means algorithm ))
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Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly
Published 2019“…This project will use fuzzy k-means clustering algorithm to cluster the data because it is easy to implement and have many advantages. …”
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Thesis -
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Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform
Published 2009“…This paper proposed the NAGE method as a straight forward transformation from sequential to parallel algorithm using domain decomposition and splitting strategies. …”
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An Educational Tool Aimed at Learning Metaheuristics
Published 2020“…In this paper, we introduce an education tool for learning metaheuristic algorithms that allows displaying the convergence speed of the corresponding metaheuristic upon setting/changing the dependable parameters. …”
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A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment
Published 2013“…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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Optimized clustering with modified K-means algorithm
Published 2021“…Among the techniques, the k-means algorithm is the most commonly used technique for determining optimal number of clusters (k). …”
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
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Improved clustering using robust and classical principal component
Published 2017“…k-means algorithm is a popular data clustering algorithm. k-means clustering aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean, serving as a prototype of the cluster. …”
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Max-D clustering K-means algorithm for Autogeneration of Centroids and Distance of Data Points Cluster
“…The experiment of the Max-D means has been conducted using synthetic data, which is taken from the Llyod’s K-Means experiments. …”
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Clustering of rainfall data using k-means algorithm
Published 2019“…Clustering algorithms in data mining is the method for extracting useful information for a given data. …”
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MaxD K-Means: A clustering algorithm for auto-generation of centroids and distance of data points in clusters
Published 2012“…The experiment of the Max-D means has been conducted using synthetic data, which is taken from the Llyod’s K-Means experiments. …”
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Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm
Published 2025“…After classifying the time set using the canopy with the K-means algorithm and the vector representation weighted by factors, the clustering impact is assessed using purity, precision, recall, and F value. …”
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Improving the tool for analyzing Malaysia’s demographic change: data standardization analysis to form geo-demographics classification profiles using k-means algorithms
Published 2016“…Clustering is one of the important methods in data exploratory in this era because it is widely applied in data mining.Clustering of data is necessary to produce geo-demographic classification where k-means algorithm is used as cluster algorithm. …”
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Spatial Clustering Algorithm for Time Series Rainfall Data Using X-Means Data Splitting
Published 2017“…Therefore, a clustering algorithm by introducing data transformation using X-means data splitting is proposed to investigate the spatial homogeneity of time series rainfall data. …”
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Development Of Machine Learning User Interface For Pump Diagnostics
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Determination of the Best Single Imputation Algorithm for Missing Rainfall Data Treatment
Published 2016“…The proposed algorithms use descriptive measures of the data, including arithmetric means, geometric means, harmonic means, medians and midranges. …”
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A web-based implementation of k-means algorithms
Published 2022“…The K-means algorithm requires two inputs for it to be applied onto a data set, the value K, and a proximity measure. …”
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Determination of the best single imputation algorithm for missing rainfall data treatment
Published 2016“…The proposed algorithms use descriptive measures of the data, including arithmetric means, geometric means, harmonic means, medians and midranges. …”
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