Search Results - (( sequence evaluation method algorithm ) OR ( based classification learning algorithm ))

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  1. 1

    Deep learning-based colorectal cancer classification using augmented and normalised gut microbiome data / Mwenge Mulenga by Mwenge , Mulenga

    Published 2022
    “…At the same time, there has been growing interest from the research community in machine learning based detection of diseases using sequence based on gut microbiome data. …”
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    Thesis
  2. 2

    Enhancement of text representation for Indonesian document summarization with deep sequential pattern mining by Dian Sa’adillah Maylawati

    Published 2023
    “…First, this study combines SPM with Sentence Scoring method as feature-based approach and Bellman-Ford algorithm as graph-based to validate the performance of SPM. …”
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    Thesis
  3. 3

    Development of a CAD system for stroke diagnosis using machine learning on DWI-MRI images by Mohd Saad, Norhashimah, Azman, Izzatul Husna, Abdullah, Abdul Rahim, Hamzah, Rostam Affendi, Muda, Ahmad Sobri, Yamba, Farzanah Atikah

    Published 2025
    “…For classification, the system evaluates traditional machine learning algorithms like support vector machine (SVM) and k-nearest neighbor (KNN), alongside deep learning models such as convolutional neural network (CNN) and bilayered neural network (BNN). …”
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    Article
  4. 4

    A coherent knowledge-driven deep learning model for idiomatic - aware sentiment analysis of unstructured text using Bert transformer by Bashar M. A., Tahayna

    Published 2023
    “…To evaluate the effectiveness of including idioms as features in sentiment analysis, we utilized advanced deep transfer learning techniques, including variants of the BERT (Bidirectional Encoder Representations from Transformers) model. …”
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    Final Year Project / Dissertation / Thesis
  5. 5

    Improving multi-resident activity recognition in smart home using multi label classification with adaptive profiling by Mohamed, Raihani

    Published 2018
    “…Nevertheless, the learning complexity of classification is increased due to the increment number of residences and activities are also intricate. …”
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    Thesis
  6. 6

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

    Published 2004
    “…CST was compared to other selected classification methods based on feature subset selection such as Induction of Decision Tree Algorithm (ID3), Base Learning Algorithm K-Nearest Nighbour Algorithm (k-NN) and NaYve Bay~sA lgorithm (NB). …”
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    Thesis
  7. 7

    Grid-Based Classifier as a Replacement for Multiclass Classifier in a Supervised Non-Parametric Approach by Moheb Pour, Majid Reza

    Published 2009
    “…The two algorithms were compared, and the proposed algorithm was found to be able to both learn and classify quickly. …”
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    Thesis
  8. 8

    Grid base classifier in comparison to nonparametric methods in multiclass classification by Moheb Pour, Majid Reza, Jantan, Adznan, Saripan, M. Iqbal

    Published 2010
    “…The two algorithms were compared, and the proposed algorithm was found to be able to both learn and classify quickly. …”
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    Article
  9. 9

    Application of genetic algorithm methods to optimize flowshop sequencing problem by Mohd Fadil, Md Sairi

    Published 2008
    “…This project will define the application of genetic algorithm method in solving flow shop sequencing problem in details and evaluate the strength and weakness of genetic algorithm method in order to optimize the optimization problem. …”
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    Undergraduates Project Papers
  10. 10

    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

    Published 2018
    “…Hence, this situation is believed in yielding of decreasing the classification accuracy. In this article, we present the exploration on the combination of the clustering based algorithm with an ensemble classification learning. …”
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    Article
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    Lexicon-based and immune system based learning methods in Twitter sentiment analysis by Jantan, Hamidah, Drahman, Fatimatul Zahrah, Alhadi, Nazirah, Mamat, Fatimah

    Published 2016
    “…The aim of this article attempts to study the potential of this method in text classification for sentiment analysis.This study consists of three phases; data preparation; classification model development using three selected Immune System based algorithms i.e. …”
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    Conference or Workshop Item
  13. 13

    Propose a New Machine Learning Algorithm based on Cancer Diagnosis by Ali, Mohammed Hasan, Kohbalan, Moorthy, Anad, Mohammed Morad, Mohammed, Mohammed Abdulameer

    Published 2018
    “…However, the traditional machine learning algorithms are facing several limitations, which may be impacted on the accuracy of classification based cancer diagnosis area. …”
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    Article
  14. 14

    Comparison and evaluation of multiple sequence alignment tools in bininformatics by Sedaghatinia, Asieh, Atan, Rodziah, Tajul Arifin, Khairina, Azmi Murad, Masrah Azrifah

    Published 2009
    “…This study addresses this critical issue in relation to MSA algorithms by systematically comparing and evaluating the functionality, usability and the algorithms of three famous multiple sequence alignment tools. …”
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    Article
  15. 15

    An automated strabismus classification using machine learning algorithm for binocular vision management system by Muhammad Amirul Isyraf, Rohismadi, Anis Farihan, Mat Raffei, Nor Saradatul Akmar, Zulkifli, Mohd. Hafidz, Ithnin, Shah Farez, Othman

    Published 2023
    “…To overcome these limitations, a machine learning algorithm, which is a case-based reasoning, is developed to automate the strabismus classification. …”
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    Conference or Workshop Item
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    Autism Spectrum Disorder Classification Using Deep Learning by Abdulrazak Yahya, Saleh, Lim Huey, Chern

    Published 2021
    “…The goal of this paper is to evaluate the deep learning algorithm for people placed in the Autism Spectrum Disorder (ASD) classification. …”
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    Article
  19. 19

    Multi-Class Multi-Level Classification of Mental Health Disorders Based on Textual Data from Social Media by Sutranggono, Abi Nizar, Sarno, Riyanarto, Ghozali, Imam

    Published 2024
    “…The Multi-Class Multi-Level (MCML) classification algorithm was applied to perform detailed classification and address the limitations of the research scope using several approaches, including machine learning, deep learning, and transfer learning approaches. …”
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    Article
  20. 20

    New Learning Models for Generating Classification Rules Based on Rough Set Approach by Al Shalabi, Luai Abdel Lateef

    Published 2000
    “…Two different models for learning in data sets were proposed based on two different reduction algorithms. …”
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    Thesis