Search Results - (( _ classification modeling algorithm ) OR ( program implementation method algorithm ))
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Classification of Google Play application using decision tree algorithm on sentiment analysis of text reviews / Aqil Khairy Hamsani, Ummu Fatihah Mohd Bahrin and Wan Dorishah Wan A...
Published 2023“…To achieve these objectives, the methods employed involve data preprocessing and implementing the Decision Tree (DT) algorithm for classification. …”
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Talent classification using support vector machine technique / Hamidah Jantan, Norazmah Mat Yusof and Mohd Hanapi Abdul Latif
Published 2014“…The objective of this study is to suggest the potential classification model for talent forecasting throughout some experiments using SVM learning algorithm. …”
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Research Reports -
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Sentiment analysis of hotel reviews using Convolutional Neural Network / Sofea Aini Mohd Sufian
Published 2021“…The prototype also been implemented using CNN model to predict the sentiment on hotel review, hi conclusion, the CNN algorithm can be used as text classification as it gives a high accuracy.…”
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Lightning fault classification for transmission line using support vector machine
Published 2023“…The proposed method was implemented in the MATLAB/SIMULINK programming platform. …”
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Early detection of heart disease using Random Forest Algorithm / Muhammad Iqbal Suhaidin ... [et al.]
Published 2023“…RFA as a machine learning classification model has the potential to provide more accurate predictions than traditional methods. …”
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BFEDroid: A Feature Selection Technique to Detect Malware in Android Apps Using Machine Learning
Published 2023“…Android (operating system); Android malware; Classification (of information); Feature Selection; Learning systems; Mobile security; Android apps; Classification models; Feature weight; Features selection; Machine learning algorithms; Machine-learning; Malware detection; Malwares; Memory usage; Selection techniques; Learning algorithms…”
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Lightning Fault Classification for Transmission Line Using Support Vector Machine
Published 2024“…The proposed method was implemented in the MATLAB/SIMULINK programming platform. …”
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Propositional satisfiability method in rough classification modeling for data mining
Published 2002“…The experimental results showed that the proposed SIPIDRIP method is a successful method in rough classification modeling. …”
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Using genetic algorithms to optimise land use suitability
Published 2012“…In this study, under environmentfriendliness objective, based on multi-agent genetic algorithms, was developed a geospatial model for the land use allocation. …”
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Implementation of Hybrid Indexing, Clustering and Classification Methods to Enhance Rural Development Programme in South Sulawesi
Published 2024“…Village development and assistance program is a strategy implemented to accelerate socio cultural development to increase the capacity of village governance and more organized administration. …”
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Prioritizing CD4 count monitoring in response to ART in resource-constrained settings: a retrospective application of prediction-based classification
Published 2012“…Methods and Findings: Using a prospective cohort of HIV-infected patients (n = 1,956) monitored upon antiretroviral therapy initiation in seven clinical sites with distinct geographical and socio-economic settings, we retrospectively apply a novel prediction-based classification (PBC) modeling method. …”
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A novel hybrid classification model of genetic algorithms, modified k-Nearest Neighbor and developed backpropagation neural network
Published 2014“…The performance of the proposed model was compared with thirteen well-known classification models based on seven datasets. …”
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An adaptive ant colony optimization algorithm for rule-based classification
Published 2020“…Various classification algorithms have been developed to produce classification models with high accuracy. …”
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Evaluation of the effectiveness and efficiency of Wagner and Fischer algorithm in retrieving Hadith translated documents / Kamarul Arifin Muhamad
Published 2002“…The result is the produced result from experiment. The method has been implemented as a C programming language. …”
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Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model
Published 2018“…The expanding of randomness layer in the traditional decision tree is able to increase the diversity of classification accuracy. However, the combination of clustering and classification algorithm might rarely be explored, particularly in the context of an ensemble classifier model. …”
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Fuzzy classification based on combinative algorithms with fuzzy similarity measure / Nur Amira Mat Saffie
Published 2019“…However, it is difficult to determine which single-model is the best classification technique in a specific application domain since a single learning algorithm may not uniformly outperform other algorithms over various datasets. …”
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Predicting breast cancer using ant colony optimisation / Siti Sarah Aqilah Che Ani
Published 2021“…This study implements a machine learning algorithm called Ant Colony Optimization (ACO) algorithm to develop an accurate classification model for predicting breast cancer cells. …”
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Formulating new enhanced pattern classification algorithms based on ACO-SVM
Published 2013“…ACO originally deals with discrete optimization problem.In applying ACO for solving SVM model selection problem which are continuous variables, there is a need to discretize the continuously value into discrete values.This discretization process would result in loss of some information and hence affects the classification accuracy and seeking time.In this algorithm we propose to solve SVM model selection problem using IACOR without the need to discretize continuous value for SVM.The second algorithm aims to simultaneously solve SVM model selection problem and selects a small number of features.SVM model selection and selection of suitable and small number of feature subsets must occur simultaneously because error produced from the feature subset selection phase will affect the values of SVM model selection and result in low classification accuracy.In this second algorithm we propose the use of IACOMV to simultaneously solve SVM model selection problem and features subset selection.Ten benchmark datasets were used to evaluate the proposed algorithms.Results showed that the proposed algorithms can enhance the classification accuracy with small size of features subset.…”
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Performance comparison of CNN and LSTM algorithms for arrhythmia classification
Published 2020“…Among the existing deep learning model, convolutional neural network (CNN) and long short-term memory (LSTM) algorithms are extensively used for arrhythmia classification. …”
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