Search Results - (( model validation bayes algorithm ) OR ( problem representation means algorithm ))

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  1. 1

    A comparative representation approach to modern heuristic search methods in a job shop by Dominic P, Dhanapal Durai, Ahmad, Kamil, Parthiban, P, Lenny Koh, SC

    Published 2008
    “…The summary of results from this article gives a conclusion that the genetic algorithm gives better results in the makespan time determination on both the job-based representation and the rulebased representation and the simulated annealing algorithm gives the better results in the mean flow time in both the representations.…”
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    Citation Index Journal
  2. 2

    Predicting hearing loss symptoms from Audiometry data using FP-Growth Algorithm and Bayesian Classifier by G. Noma, Nasir, Mohd Khanapi, Abd Ghani, Mohamad Khir , Abdullah, Noorizan , Yahya

    Published 2013
    “…Both multivariate Bernoulli and multinomial naïve Bayes models were used with and without the feature extraction. …”
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    Article
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    Advanced data mining techniques for landslide susceptibility mapping by Ibrahim, M.B., Mustaffa, Z., Balogun, A.-L., Hamonangan Harahap, I.S., Ali Khan, M.

    Published 2021
    “…The indices indicated that the SVM model performed better than the other two algorithms in both training and validation datasets. …”
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    Article
  5. 5

    Pemahaman guru matematik Tahun Enam tentang pembahagian nombor bulat / Hoi Sim Min by Hoi , Sim Min

    Published 2018
    “…Data was collected through five clinical interviews involving mental images, representations, meaning, reasoning and problem solving, which was captured on video. …”
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    Thesis
  6. 6

    MODELLING ANALYSIS FOR ACCURATE TROPICAL WEATHER FORECASTING by Calvin, Wong Qin Jie

    Published 2023
    “…The Random Forest, K-Nearest Neighbors, Support Vector Machines, XGBoost and Naïve Bayes algorithm is proposed to validate the model for rainfall prediction, which is proven to operate well with excellent accuracy in previous researches. …”
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    Final Year Project Report / IMRAD
  7. 7

    Novice programmers’ emotion and competency assessments using machine learning on physiological data / Fatima Jannat by Fatima, Jannat

    Published 2022
    “…Hyper-parameter tuning has been used in all the algorithms using k-fold cross validation to have the best accuracy and to avoid the over-fitting issue. …”
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    Thesis
  8. 8

    Hybrid multiobjective genetic algorithm for integrated dynamic scheduling and routing of jobs and automated guided vehicles in flexible manufacturing systems by Umar, Umar Ali

    Published 2014
    “…Genetic algorithm has recorded of huge success in solving NP-Complete optimization problems with similar nature to this problem. …”
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    Thesis
  9. 9

    USING LATENT SEMANTIC INDEXING FOR DOCUMENT CLUSTERING by MUFLIKHAH, LAILIL

    Published 2010
    “…Based on the new representation, the documents are then subjected to the clustering algorithm itself, which is Fuzzy c-Means algorithm. …”
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    Thesis
  10. 10

    Sentiment Analysis of Sexual Harassment in Malaysia on Twitter Using Machine Learning Algorithms by Nurellezia, Suleiman

    Published 2023
    “…The transformed data is then modelled using machine learning algorithms such as Naïve Bayes classifier and Support Vector Machine to predict the overall sentiment of tweets, in which the finding depicted an overall positive sentiment surrounding the issue. …”
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    Final Year Project Report / IMRAD
  11. 11

    A comparative analysis of machine learning algorithms for diabetes prediction by Alansari, Waseem Abdulmahdi, Masnizah Mohd

    Published 2024
    “…The methodology involves data collection, pre-processing, and training the algorithms using k-fold cross-validation. The results indicate that pre-processing steps and dataset characteristics significantly impact algorithm performance. …”
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    Article
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    Mobile app of mood prediction based on menstrual cycle using machine learning algorithm / Nur Hazirah Amir by Amir, Nur Hazirah

    Published 2019
    “…It implemented Supervised Learning algorithm with Bayes’ Theorem model for the calculation of mood prediction using Python programming language. …”
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    Thesis
  14. 14

    GIS-based air quality modelling: spatial prediction of PM10 for Selangor State, Malaysia using machine learning algorithms by Tella, A., Balogun, A.-L.

    Published 2021
    “…Spatially processed data such as NDVI, SAVI, BU, LST, Ws, slope, elevation, and road density was used for the modelling. The model was trained with 70 of the dataset, while 30 was used for cross-validation. …”
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    Article
  15. 15

    Crossover and mutation operators of real coded genetic algorithms for global optimization problems by Lim, Siew Mooi

    Published 2016
    “…This study is primarily aimed at investigating two issues in genetic algorithm (GA) and one issue in conformational search (CS) problems. …”
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    Thesis
  16. 16

    Prediction of novel doping agent through the integration of chemical and biological data using in silico method by Mohd Rosman, Nurul Ain

    Published 2016
    “…Two validations were performed on the models which are internal and external validation. …”
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    Student Project
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    In silico prediction of novel doping agent through the integration of chemical and phenotypic data by Raduan, Muhammad Artif

    Published 2016
    “…The internal validation showed that the combination of MACCS and Naive Bayes model performed best with a sensitivity value of 0.5950 when a cut off of rank 5 was applied. …”
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    Student Project
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    Analyzing customer reviews for ARBA Travel using sentiment analysis by Abdullah, Nurulain

    Published 2025
    “…Three machine learning algorithms which are Naive Bayes, Logistic Regression, and Support Vector Machine, were implemented and evaluated using cross-validation and performance metrics such as accuracy, precision, recall, and F1- score. …”
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    Student Project
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    Occupancy grid map algorithm with neural network using array of infrared sensors by N A, Yatim, N, Buniyamin, Z M, Noh, Nur Aqilah, Othman

    Published 2020
    “…From the simulation experiments, it is observed that, that neural network-integrated algorithm has a better map estimate throughout robot’s navigation with mean of 28% more accurate compared to occupancy grid map algorithm without neural network. …”
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    Conference or Workshop Item