Search Results - (( java application learning algorithm ) OR ( data evaluation means algorithm ))
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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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Thesis -
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Efficient genetic partitioning-around-medoid algorithm for clustering
Published 2019“…These algorithms mostly built upon the partitioning k-means clustering algorithm. …”
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Performance evaluation of different data aggregation algorithms for different types of sensors in WSN based cluster
Published 2018“…The algorithms applied separately with (1) Mean (2) Median (3) Mode (4) Geometric mean (5) Harmonic mean. …”
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Analysis of K-Mean and X-Mean Clustering Algorithms Using Ontology-Based Dataset Filtering
Published 2021“…Our methodology incorporated ontology to filter the datasets and exploited Rapidminer environment to evaluate the performance of clustering algorithms. …”
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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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Neural Networks Ensemble: Evaluation of Aggregation Algorithms for Forecasting
Published 2013“…The performances ofthese aggregation algorithms ofNNs ensemble were evaluated with the mean absolutepercentage error and symmetric mean absolute percentage error. …”
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An observation of different clustering algorithms and clustering evaluation criteria for a feature selection based on linear discriminant analysis
Published 2022“…Yet, the LDA cannot be implemented directly on unsupervised data as it requires the presence of class labels to train the algorithm. …”
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Book Chapter -
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Development Of Machine Learning User Interface For Pump Diagnostics
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Monograph -
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Centre-based hard clustering algorithms for Y-STR data / Ali Seman, Zainab Abu Bakar and Azizian Mohd. Sapawi
Published 2010“…The three algorithms above are experimented and evaluated in partitioning Y-STR haplogroups and Y-STR Surname data. …”
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Improved stochastic gradient descent algorithm with mean-gradient adaptive stepsize for solving large-scale optimization problems
Published 2023“…It is an iterative algorithm with descent properties that reduces computational cost by using derivatives of random data points. …”
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Segmentation of MRI brain images using statistical approaches
Published 2011“…Noise is one of the obstacles for brain MRI segmentation. The non-Local means (NL-means) algorithm is a state-of-the art neighbourhood-based noisereduction method which is time-consuming and its accuracy can be improved. …”
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Algorithmic approaches in model selection of the air passengers flows data
Published 2015“…Algorithm is an important element in any problem solving situation.In statistical modelling strategy, the algorithm provides a step by step process in model building, model testing, choosing the ‘best’ model and even forecasting using the chosen model.Tacit knowledge has contributed to the existence of a huge variability in manual modelling process especially between expert and non-expert modellers.Many algorithms (automated model selection) have been developed to bridge the gap either through single or multiple equation modelling.This study aims to evaluate the forecasting performances of several selected algorithms on air passengers flow data based on Root Mean Square Error (RMSE) and Geometric Root Mean Square Error (GRMSE).The findings show that multiple models selection performed well in one and two step-ahead forecast but was outperformed by single model in three step-ahead forecasts.…”
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Conference or Workshop Item -
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…Hybridizing the Deep Neural Network (DNN) with the K-Means Clustering algorithm will increase the accuracy and reduce the data complexity of the Lorenz dataset. …”
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Neural network ensemble: Evaluation of aggregation algorithms in electricity demand forecasting
Published 2013“…The predictive performance of these algorithms are evaluated using Australian electricity demand data. …”
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Neural network ensemble: Evaluation of aggregation algorithms in electricity demand forecasting
Published 2013“…The predictive performance of these algorithms are evaluated using Australian electricity demand data. …”
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Neural network ensemble: Evaluation of aggregation algorithms in electricity demand forecasting
Published 2013“…The predictive performance of these algorithms are evaluated using Australian electricity demand data. …”
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AI powered asthma prediction towards treatment formulation: an android app approach
Published 2022“…TensorFlow is utilized to integrate machine learning with an Android application. We accomplished asthma therapy using an Android application developed in Java and running on the Android Studio platform.…”
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