Search Results - (( data classification using algorithm ) OR ( pattern extraction learning algorithm ))

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  1. 1

    Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition by Leong, Shi Xiang

    Published 2017
    “…The result has shown that the proposed integration system could be applied to increase the performance of the classification. However, further study is needed in the feature extraction and clustering algorithms part as the performance of the pattern classification is still depending on the data input.…”
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    Thesis
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    A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani by Mahmoud Reza, Saybani

    Published 2016
    “…Many researchers, who have developed methods and algorithms within the field of artificial intelligence, machine learning and data mining, have addressed extracting useful information from the data. …”
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    Thesis
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    Development of a scaled conjugate gradient algorithm for significant RF neural signal processing by Mohd Norden, Muhammad Farid Akmal, Mohd Isa, Roshakimah, Mohd Isa, Mohd Roshalizi, S. Abdul Kadir, Ros Shilawani, Md Azli, Muhammad Hariz, Muhammad Akram, Amir Syarif

    Published 2025
    “…This study aims to improve the classification of RF neural data patterns using SCG. EEG neural data was captured in sessions before, during and after RF exposure. …”
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    Article
  6. 6

    Rough Neural Networks Architecture For Improving Generalization In Pattern Recognition by Ali Adlan, Hanan Hassan

    Published 2004
    “…The algorithm enhances the recognition ability of the system compared to manual extraction and labeling of pattern classes. …”
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    Thesis
  7. 7

    Classification of Students' Performance in Computer Programming Course According to Learning Style by Norwawi, NM, Abdusalam, SF, Hibadullah, CF, Shuaibu, BM

    Published 2024
    “…Previous studies examined some of the variables influencing students' performance using statistical data analysis. The critical point of this study is the use of classification algorithm to extract patterns which are examined from the cognitive factor specific learning style. …”
    Proceedings Paper
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    Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining. by Saeed, Walid

    Published 2005
    “…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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    Thesis
  10. 10

    Plant recognition based on identification of leaf image using image processing / Nor Silawati Sha’ari by Sha’ari, Nor Silawati

    Published 2018
    “…For the ANN, Multilayer feed-forward networks are trained using Back Propagation (BP) learning algorithm and for the KNN, is used the most common distance which is Euclidean. …”
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    Student Project
  11. 11

    APPLICATION OF LINK GRAMMAR IN SEMI-SUPERVISED NAMED ENTITY RECOGNITION FOR ACCIDENT DOMAIN by SARI, YUNITA SARI

    Published 2011
    “…The Self-Training algorithm greatly benefits semi-supervised learning which allows classification of entities given only a small-size of labelled data. …”
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    Thesis
  12. 12

    Data Mining for Building Neural Protein Sequence Classification Systems with Improved Performance by Wang, Dianhui, Lee, Nung Kion, Dillon, Tharam S.

    Published 2003
    “…Traditionally, two protein sequences are classified into the same class if their feature patterns have high homology. These feature patterns were originally extracted by sequence alignment algorithms, which measure similarity between an unseen protein sequence and identified protein sequences. …”
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    Proceeding
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    Decoding of visual activity patterns from fMRI responses using multivariate pattern analyses and convolutional neural network by Zafar, R., Kamel, N., Naufal, M., Malik, A.S., Dass, S.C., Ahmad, R.F., Abdullah, J.M., Reza, F.

    Published 2017
    “…In this study, an algorithm is developed using Multivariate pattern analysis (MVPA) and modified CNN to decode the behavior of brain for different images with limited data set. …”
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    Article
  14. 14

    Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan by Meisam , Gordan

    Published 2020
    “…In the modeling phase, amongst all DM algorithms, the applicability of machine learning, artificial intelligence and statistical data mining techniques were examined using Support Vector Machine (SVM), Artificial Neural Network (ANN) and Classification and Regression Tree (CART) to detect the hidden patterns in vibration data. …”
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    Thesis
  15. 15

    The classification of motor imagery response: an accuracy enhancement through the ensemble of random subspace k-NN by Rashid, Mamunur, Bari, Bifta Sama, Hasan, Md Jahid, Mohd Azraai, Mohd Razman, Rabiu Muazu, Musa, Ahmad Fakhri, Ab. Nasir, Anwar, P. P. Abdul Majeed

    Published 2021
    “…In the present investigation, an ensemble learning-based classification algorithm, namely random subspace k-nearest neighbour (k-NN) has been proposed to classify the motor imagery (MI) data. …”
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    Article
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    A review on sentiment analysis model Chinese Weibo text by Dawei Wang, Rayner Alfred

    Published 2020
    “…In feature extraction, the Lexicon-based Model, Machine learning Model and deep learning Model usually was used. …”
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    Proceedings
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    Common spatial pattern with feature scaling (FSc-CSP) for motor imagery classification by Prathama, Y.B.H., Shapiai, M.I., Aris, S.A.M., Ibrahim, Z., Jaafar, J., Fauzi, H.

    Published 2017
    “…In this paper, we propose an algorithm called Feature Scaling Common Spatial Pattern (FSc-CSP) to overcome the problem of feature selection. …”
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    Article
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    Classification of stock market index based on predictive fuzzy decision tree by Khokhar, Arashid Hafeez

    Published 2005
    “…In particular, predictive FDT algorithm is based on the concept of degree of importance of attribute contributing to the classification. …”
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    Thesis
  20. 20

    Deep plant: A deep learning approach for plant classification / Lee Sue Han by Lee , Sue Han

    Published 2018
    “…They look for the procedures or algorithms that maximize the use of leaf databases for plant predictive modelling, but this results in leaf features which are liable to change with different leaf data and feature extraction techniques. …”
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    Thesis