Search Results - (( _ classification modelling algorithm ) OR ( program implementation based algorithm ))

Predicting Student Performance in Object Oriented Programming Using Decision Tree : A Case at Kolej Poly-Tech Mara, Kuantan by Mohd Hanis, Rani, Abdullah, Embong

“…The objective was to identify and implement the most accurate algorithm for the KPTM dataset and to come up with a good prediction model using decision tree technique. …”
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Lightning fault classification for transmission line using support vector machine by Asman, Saidatul Habsah, Ab Aziz, Nur Fadilah, Ab Kadir, Mohd Zainal Abidin, Ungku Amirulddin, Ungku Anisa, Roslan, Nurzanariah, Elsanabary, Ahmed

“…The classification performance of the developed algorithms was evaluated using confusion matrix. …”
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BFEDroid: A Feature Selection Technique to Detect Malware in Android Apps Using Machine Learning by Chimeleze C., Jamil N., Ismail R., Lam K.-Y., Teh J.S., Samual J., Akachukwu Okeke C.

“…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…”

Lightning Fault Classification for Transmission Line Using Support Vector Machine by Asman S.H., Aziz N.F.A., Kadir M.Z.A.A., Amirulddin U.A.U., Roslan N., Elsanabary A.

“…The classification performance of the developed algorithms was evaluated using confusion matrix. …”

Classification and visualization on eligibility rate of applicant’s LinkedIn account using Naïve Bayes / Nurul Atirah Ahmad, Khyrina Airin Fariza Abu Samah and Nuwairah Aimi Ahmad... by Ahmad, Nurul Atirah, Abu Samah, Khyrina Airin Fariza, Ahmad Kushairi, Nuwairah Aimi

“…This project implements the Naive Bayes algorithm as the classification algorithm. The classification is set to two categories: Eligible or Ineligible. …”
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Using genetic algorithms to optimise land use suitability by Pormanafi, Saeid

“…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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A stylometry approach for blind linguistic steganalysis model against translation-based steganography by Mohd Lokman, Syiham

“…This is because all translated in TBS text have an intrinsic structural styles that can be used to improve the performance of a blind steganalysis model. The proposed stylometry-based blind steganalysis model consists of two stages, which are stylometric feature selection and classification. …”
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Development of deep learning based user-friendly interface for fruit quality detection by Mohd Ali, Maimunah, Hashim, Norhashila

“…The implementation of deep learning algorithms has contributed to various applications related to the detection of fruit quality. …”
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Classification and visualization of Malaysian fast food restaurant chain based on twitter sentiment analysis / Muhammad Hafeez Hakimi Muhd Zahidi Ridzuan by Muhd Zahidi Ridzuan, Muhammad Hafeez Hakimi

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Implementation of Hybrid Indexing, Clustering and Classification Methods to Enhance Rural Development Programme in South Sulawesi by Muhammad, Faisal

“…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 by Azzoni, Livio, Foulkes, Andrea S., Liu, Yan, Johnson, Margaret, Smith, Collette, Kamarulzaman, Adeeba, Montaner, Julio, Mounzer, Karam, Saag, Michael, Cahn, Pedro, Cesar, Carina, Krolewiecki, Alejandro, Sanne, Ian, Montaner, Luis J.

“…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. The model uses repeatedly measured biomarkers (white blood cell count and lymphocyte percent) to predict CD4+ T cell outcome through first-stage modeling and subsequent classification based on clinically relevant thresholds (CD4+ T cell count of 200 or 350 cells/ml). …”
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A novel hybrid classification model of genetic algorithms, modified k-Nearest Neighbor and developed backpropagation neural network by Salari, Nader, Shohaimi, Shamarina, Najafi, Farid, Nallappan, Meenakshii, Karishnarajah, Isthrinayagy

“…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 by Al-Behadili, Hayder Naser Khraibet

“…Various classification algorithms have been developed to produce classification models with high accuracy. …”
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Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model by Sulaiman, Md. Nasir, Mohamed, Raihani, Mustapha, Norwati, Zainudin, Muhammad Noorazlan Shah

“…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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Implementation of Autonomous Vehicle Navigation Algorithms Using Event-Driven Programming by Saman, Abu Bakar Sayuti, Sebastian , Patrick, Malek, Nadhira, Hasidin, Nurul Zahidah

“…The objective of this paper is to describe the implementation of autonomous navigation through the use of event-driven programming technique which was based on finite state machines (FSM). …”
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Fuzzy classification based on combinative algorithms with fuzzy similarity measure / Nur Amira Mat Saffie by Mat Saffie, Nur Amira

“…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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Pairwise testing tools based on hill climbing algorithm (PTCA) by Lim, Seng Kee

“…The actual implementation of the algorithm which is in Java programming language, the program is implemented on Net Bean 7.0.1. …”
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Predicting breast cancer using ant colony optimisation / Siti Sarah Aqilah Che Ani by Che Ani, Siti Sarah Aqilah

“…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 by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…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 by Hassan, S.U., Zahid, M.S.M., Husain, K.

“…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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