Search Results - (( process learning tree algorithm ) OR ( java application using 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
    “…This work employed the use of machine learning approach. Four conventional classification algorithms: naïve bayes (NB), support vector machines (SVM), nearest neighbor (k-NN), and decision trees (J48) classifiers are implemented in identifying and categorizing tweet data of three political figures in Malaysia: Dato Seri Anwar, Dato Hadi Awang, and Lim Guang Eng, as either positive, negative, or neutral perceptions. …”
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    Thesis
  2. 2

    E4ML: Educational Tool for Machine Learning by Sainin, Mohd Shamrie, Siraj, Fadzilah

    Published 2003
    “…There are various types of machine learning algorithms with certain processes taken by the algorithm.In teaching of the machine learning algorithms, such processes need to be explained especially to the beginner in introductory level.This paper discusses the development the tool that addresses the process by certain algorithm to produce a hypothesis or output based on given data.This tool can also be used in teaching and learning purposes.The explanation of processes by the algorithms is demonstrated through simple simulation.The source of the algorithms was adapted from Mitchell book [1] that cover popular algorithms in machine learning for teaching and learning such as Concept Learning, Decision Tree, Bayesian Learning, Neural Networks, and Instance based Learning.The tool also used several classes of Weka (Waikato Environment for Knowledge Analysis) as a basis for the design and implementation of the new tool that focuses on explaining the processes taken by certain algorithm.…”
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    Conference or Workshop Item
  3. 3

    Parse tree visualization for Malay sentence (BMTutor) by Muhamad Noor, Yusnita, Jamaludin, Zulikha

    Published 2015
    “…It is also to enhance the learning process in BM that can be used by communities, especially students. …”
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    Article
  4. 4

    Waste management using machine learning and deep learning algorithms by Sami, Khan Nasik, Amin, Zian Md Afique, Hassan, Raini

    Published 2020
    “…For our research we did the comparisons between three Machine Learning algorithms, namely Support Vector Machine (SVM), Random Forest, and Decision Tree, and one Deep Learning algorithm called Convolutional Neural Network (CNN), to find the optimal algorithm that best fits for the waste classification solution. …”
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    Article
  5. 5

    Interaction effect of process parameters and Pd-electrocatalyst in formic acid electro-oxidation for fuel cell applications: Implementing supervised machine learning algorithms by Hossain S.K.S., Ali S.S., Rushd S., Ayodele B.V., Cheng C.K.

    Published 2023
    “…Carbon nanotubes; Electrocatalysts; Electrooxidation; Forestry; Formic acid; Gaussian distribution; Learning algorithms; Palladium; Parameter estimation; Regression analysis; Support vector machines; Formic acid electrooxidation; Fuel cell application; Gaussian kernel functions; Gaussian process regression; Interaction effect; Machine learning algorithms; Performance; Process parameters; Regression trees; Support vector machine regressions; Sensitivity analysis…”
    Article
  6. 6

    Performance evaluation for different intrusion detection system algorithms using machine learning by Zarir, Mustafa Nadhim

    Published 2018
    “…The objectives of this project is to evaluate the performance of various intrusion detection algorithms based on machine learning. The algorithms considered are the Naive Bays Algorithm, Decision Tree Algorithm and Hybrid Algorithm for different datasets. …”
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    Thesis
  7. 7

    Prediction of Oil Palm Yield Using Machine Learning in the Perspective of Fluctuating Weather and Soil Moisture Conditions: Evaluation of a Generic Workflow by Khan N., Kamaruddin M.A., Ullah Sheikh U., Zawawi M.H., Yusup Y., Bakht M.P., Mohamed Noor N.

    Published 2023
    “…Selected regression models were compared with Random Forest, Gradient Boosting, Decision Tree, and other non-tree algorithms to prove the R2 driven performance superiority of tree-based ensemble models. …”
    Article
  8. 8

    Application of Decision Trees in Athlete Selection: A Cart Algorithm Approach by Riska Wahyu, Romadhonia, A'yunin, Sofro, Danang, Ariyanto, Dimas Avian, Maulana, Junaidi Budi, Prihanto

    Published 2023
    “…The focus of this study is on the use of DTs, employing the Classification and Regression Trees (CART) algorithm, in the initial screening of athletes. …”
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    Article
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    Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd by Nur Farahaina, Idris

    Published 2022
    “…ID3 has the most advantages among the three algorithms, especially in processing time, as it builds the fastest tree with short depth. …”
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    Thesis
  11. 11

    RSA Encryption & Decryption using JAVA by Ramli, Marliyana

    Published 2006
    “…References and theories to support the research of 'RSA Encryption/Decryption using Java' have been disclosed in Literature Review section. …”
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    Final Year Project
  12. 12

    Machine Learning Regression Approach for Estimating Energy Consumption of Appliances in Smart Home by Husin N.S.I.M., Mostafa S.A., Jaber M.M., Gunasekaran S.S., Al-Shakarchi A.H., Abdulsattar N.F.

    Published 2024
    “…To achieve this, three machine learning algorithms, namely Decision Forest (DF), Boosted Decision Tree (BDT), and Linear Regression (LR), were chosen for regression tasks to estimate the energy consumption of several appliances accurately. …”
    Conference Paper
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    Enhanced faster region-based convolutional neural network for oil palm tree detection by Liu, Xinni

    Published 2021
    “…Hence, this research aims to close the research gaps by exploring the deep learning-based object detection algorithm and the classical convolutional neural network (CNN) to build an automatic deep learning-based oil palm tree detection and counting framework. …”
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    Thesis
  14. 14

    Application Of Multi-Layer Perceptron Technique To Detect And Locate The Base Of A Young Corn Plant by Morshidi, Malik Arman

    Published 2007
    “…Results of studying color segmentation using machine-learning algorithm and color space analysis is presented in this thesis. …”
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    Thesis
  15. 15

    Edge assisted crime prediction and evaluation framework for machine learning algorithms by Adhikary, Apurba, Murad, Saydul Akbar, Munir, Md Shirajum, Choong Seon, Hong Seong

    Published 2022
    “…To anticipate occurrences, ML methods such as Decision Trees, Neural Networks, K-Nearest Neighbors, and Impact Learning are being utilized, and their performance is compared based on the data processing and modification used. …”
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    Conference or Workshop Item
  16. 16

    Defect green coffee bean detection using image recognition and supervised learning by Shafian Izan Sofian

    Published 2022
    “…Therefore, in this research project, the process will be conducted by using an image classifier with the model of a machine learning algorithm which the candidates comprise of Support Vector Machine, k-Nearest Neighbour and Decision Tree. k-nearest neighbour has the highest F1-score (0.51) than the other two algorithms (Support Vector Machine: 0.50, and Decision Tree: 0.48). …”
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    Academic Exercise
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    Breast cancer disease classification using fuzzy-ID3 algorithm with FUZZYDBD method: automatic fuzzy database definition by Nur Farahaina, Idris, Mohd Arfian, Ismail

    Published 2021
    “…FID3 algorithm combined the fuzzy system and decision tree techniques with ID3 algorithm as the decision tree learning. …”
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    Article
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    Mobile Learning: An Application Prototype for AVL Tree Learning Object by Ibrahim, Mohammad Noor, Mahamad, Saipunidzam, Chua, Edrea Ning Wei

    Published 2010
    “…This application intends to complement the current traditional classroom and e-learning systems. Initial testing has shown that a well-presented video clip of AVL tree concept that delivered through mobile phone has a great potential to promote and enhance learning process.…”
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    Conference or Workshop Item