Search Results - (( java implementation learning algorithm ) OR ( using data learning algorithm ))

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  1. 1

    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

    Published 2022
    “…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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  2. 2

    A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment by Ruzita, Ahmad

    Published 2013
    “…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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  3. 3

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

    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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  4. 4

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

    Published 2016
    “…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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    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm by Norulazmi, Kasim

    Published 2008
    “…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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  7. 7

    A malware analysis and detection system for mobile devices / Ali Feizollah by Ali, Feizollah

    Published 2017
    “…We extracted 30 different features from network traffic. We then used feature selection algorithms and deep learning algorithms to build a detection model. …”
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  8. 8

    Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions by Saraswati, Galuh Wilujeng

    Published 2017
    “…In conclusion, diabetic ketoacidosis in unrestricted food intake conditions can be predicted using the proposed ANFIS and GA-ANFIS model. Future work should be focusing on data collection of the E-Nose sensors and the improvement of the learning algorithm robustness towards environmental noise during data acquisition, such as evaporation and contamination of odor samples.…”
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  9. 9

    An Educational Tool Aimed at Learning Metaheuristics by Kader, Md. Abdul, Jamaluddin, Jamal A., Kamal Z., Zamli

    Published 2020
    “…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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    Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy by Ganesh , Krishnasamy

    Published 2019
    “…As for classification, researchers have used semi-supervised learning for extreme learning machine (ELM), where they have exploited both the labeled and unlabeled data in order to boost the learning performances. …”
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  12. 12

    Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process by Ali Al-Assadi, Hayder M. A.

    Published 2004
    “…The design network is trained by presenting several target machining data that the network must learn according to a learning rule (algorithm). …”
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  13. 13

    Impact learning: A learning method from feature's impact and competition by Prottasha, Nusrat Jahan, Murad, Saydul Akbar, Abu Jafar, Md Muzahid, Rana, Masud, Kowsher, Md, Adhikary, Apurba, Biswas, Sujit, Bairagi, Anupam Kumar

    Published 2023
    “…A variety of well-known machine learning algorithms have been developed for use in the field of computer science to analyze data. …”
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    Article
  14. 14

    Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection by Tubishat, Mohammad, Idris, Norisma, Shuib, Liyana, Abushariah, Mohammad A.M., Mirjalili, Seyedali

    Published 2020
    “…These problems will occur because these fields are mainly used machine learning classifiers. However, machine learning accuracy is affected by the noisy and irrelevant features. …”
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    Article
  15. 15

    Octane number prediction for gasoline blends using convolution neural network / Zhu Yue by Zhu , Yue

    Published 2021
    “…Machine performance learning models depend to a large extant to the data quality used train the model. …”
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    SLIDING WINDOW TRAINING ALGORITHMS USING MLP-NETWORK FOR CORRELATED AND LOST PACKET DATA by AHMED IZZELDIN, HUZAIFA TAWFEIG

    Published 2012
    “…This thesis gives a systematic investigation of various MLP learning mainly Sliding Window (SW) learning mode which is treated as the adaptation of offline algorithms into online application Consequently this thesis reviews various offline algorithms including: batch backpropagation, nonlinear conjugate gradient, limited memory and full-memory Broyden, Fletcher, Goldfarb and Shanno algorithms and different forms of the latest proposed bimary ensemble learning. …”
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  18. 18

    Comparative performance of deep learning and machine learning algorithms on imbalanced handwritten data by Amri, A’inur A’fifah, Ismail, Amelia Ritahani, Zarir, Abdullah Ahmad

    Published 2018
    “…The experiment shows that although the algorithm is stable and suitable for multiple domains, the imbalanced data distribution still manages to affect the outcome of the conventional machine learning algorithms.…”
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    Article
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    Novice programmers’ emotion and competency assessments using machine learning on physiological data / Fatima Jannat by Fatima, Jannat

    Published 2022
    “…There is also growing interest in modeling machine learning and deep learning algorithms that can learn from user’s data, understand and react to that individual’s affective state. …”
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  20. 20

    Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

    Published 2004
    “…One of the problems addressed by machine learning is data classification. Finding a good classification algorithm is an important component of many data mining projects. …”
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