Search Results - (( java implementation learning algorithm ) OR ( basic learning tree algorithm ))

Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm by Norulazmi, Kasim

“…The prototype system, known as Java Plagiarism Detection System (JPDS) implements the Greedy-String-Tiling algorithm to detect similarities among tokens in a Java source code files. …”
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Application Of Multi-Layer Perceptron Technique To Detect And Locate The Base Of A Young Corn Plant by Morshidi, Malik Arman

“…Results of studying color segmentation using machine-learning algorithm and color space analysis is presented in this thesis. …”
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An Educational Tool Aimed at Learning Metaheuristics by Kader, Md. Abdul, Jamaluddin, Jamal A., Kamal Z., Zamli

“…Implemented with Java, this tool provides a friendly GUI for setting the parameters and display the result from where the learner can see how the selected algorithm converges for a particular problem solution. …”
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

“…The method was implemented using Java and the results of the simulation were evaluated using five standard performance metrics: accuracy, AUC, precision, recall, and f-Measure. …”
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A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment by Ruzita, Ahmad

“…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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Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly by Zulkifly, Ahmad Zuladzlan

“…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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Estimation of electric vehicle turning radius through machine learning for roundabout cornering by Ashaa, Supramaniam, Muhammad Aizzat, Zakaria, Kunjunni, Baarath, Mohamad Heerwan, Peeie, Ahmad Fakhri, Ab. Nasir, Muhammad Izhar, Ishak

“…This paper presents an alternative approach for estimating the turning radius using machine learning technique. While on-board sensors are unable to offer adequate information on vehicle states to the algorithm, vehicle states other than those directly detected by on-board sensors can be inferred using machine learning (ML) approaches based on the collected data. …”
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Landslide Susceptibility Mapping with Stacking Ensemble Machine Learning by Solihin M.I., Yanto, Hayder G., Maarif H.A.-Q.

“…One of the prominent methods to improve machine learning accuracy is by using ensemble method which basically employs multiple base models. …”

Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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A stacked ensemble deep learning model for water quality prediction / Wong Wen Yee by Wong , Wen Yee

“…Any resampling algorithm is not a necessity in the case of this proposed algorithm. …”
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Talkout : Protecting mental health application with a lightweight message encryption by Gavin Teo Juen

“…The investigation of lightweight message encryption algorithms is conducted with systematic quantitative literature and experiment implementation in Java and Android running environment. …”
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Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform by Alias, Norma, Satam, Noriza, Abd. Ghaffar, Zarith Safiza, Darwis, Roziha, Hamzah, Norhafiza, Islam, Md. Rajibul

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Automatic extraction of digital terrain model and Building Footprint from airborne LiDAR data using rule-based learning techniques by Jifroudi, Hamidreza Maskani

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Empirical study on intelligent android malware detection based on supervised machine learning by Abdullah, Talal A.A., Ali, Waleed, Abdulghafor, Rawad Abdulkhaleq Abdulmolla

“…More significantly, this paper empirically discusses and compares the performances of six supervised machine learning algorithms, known as K-Nearest Neighbors (K-NN), Decision Tree (DT), Support Vector Machine (SVM), Random Forest (RF), Naïve Bayes (NB), and Logistic Regression (LR), which are commonly used in the literature for detecting malware apps.…”
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A deep learning approach: The impact of sentiment analysis of Bangladeshi workers over the world by Tomal, Md Raihanul Islam, Kader, Tanveer, Kohbalan, Moorthy, Mazlina, Abdul Majid

“…TF-IDF vectorization was used for feature extraction, followed by basic machine learning algorithms such as Decision Tree, Support Vector Machine, and Naive Bayes. …”
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Text-based emotion prediction system using machine learning approach by Ahmad Fakhri, Ab. Nasir, Eng, Seok Nee, Chun, Sern Choong, Ahmad Shahrizan, Abdul Ghani, Anwar, P. P. Abdul Majeed, Asrul, Adam, Mhd, Furqan

“…Therefore, four supervised machine learning classification algorithms such as Multinomial Naïve Bayes, Support Vector Machine, Decision Trees, and kNearest Neighbors were investigated. …”
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Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining. by Saeed, Walid

“…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
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Deep learning-based breast cancer detection and classification using histopathology images / Ghulam Murtaza by Ghulam , Murtaza

“…The extracted features are evaluated through six machine learning (ML) classifiers namely softmax, k-nearest neighbor (kNN), support vector machine, linear discriminant analysis, decision tree, and naive Bayes. …”
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Predictive modeling and feature attribution of CO₂ adsorption on LDH-derived materials using machine learning approach by Pinto, Mavin Jason, Sharath, S. S., Sudhakar, K., Priya, S. Shanmuga, Thirunavukkarasu, I.

“…We report the application of six machine learning models, namely Random Forest (RF), gradient boosting decision tree (GBDT), extreme gradient boosting (XGBoost), Light gradient boosting machine (LightGBM), categorical boosting (CatBoost), and Adaptive boosting (AdaBoost) to predict CO2 adsorption capacity on LDH-derived materials. …”
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A malware analysis and detection system for mobile devices / Ali Feizollah by Ali, Feizollah

“…We then used feature selection algorithms and deep learning algorithms to build a detection model. …”
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