Search Results - (( sequence classification _ algorithm ) OR ( pattern classification learning algorithm ))

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  1. 1

    Genetic ensemble biased ARTMAP method of ECG-Based emotion classification by Loo, C.K., Liew, W.S., Sayeed, M.S.

    Published 2012
    “…The proposed system utilizes Biased ARTMAP for pattern learning and classification. The ARTMAP system is dependent on training sequence presentation to determine the effectiveness of the learning processes, as well as the strength of the biasing parameter, lambda λ. …”
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    Extraction and Optimization of Fuzzy Protein Sequences Classification Rules Using GRBF Neural Networks by Wang, Dianhui, Lee, Nung Kion, Dillon, Tharam S.

    Published 2003
    “…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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    Article
  3. 3

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

    Published 2003
    “…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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    A review on data stream classification by A. A, Haneen, A., Noraziah, Abd Wahab, Mohd Helmy

    Published 2018
    “…As such the typical tasks of searching data have been linked to streams of data that are inclusive of clustering, classification, and repeated mining of pattern. This paper presents several data stream clustering approaches, which are based on density, besides attempting to comprehend the function of the related algorithms; both semi-supervised and active learning, along with reviews of a number of recent studies.…”
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    Article
  6. 6

    A Review on Data Stream Classification by A. A., Haneen, Noraziah, Ahmad, Mohd Helmy, Abd Wahab

    Published 2018
    “…As such the typical tasks of searching data have been linked to streams of data that are inclusive of clustering, classification, and repeated mining of pattern. This paper presents several data stream clustering approaches, which are based on density, besides attempting to comprehend the function of the related algorithms; both semi-supervised and active learning, along with reviews of a number of recent studies.…”
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  7. 7

    Adaptive Feature Selection and Image Classification Using Manifold Learning Techniques by ASHRAF, AMNA, MOHD NAWI, NAZRI, MUHAMMAD AAMIR, MUHAMMAD AAMIR

    Published 2024
    “…Clustering algorithms such as K-means, spectral clustering, and the Gaussian Mixer Model have been tested with manifold learning approaches for adaptive feature selection. …”
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  8. 8

    Probabilistic ensemble fuzzy ARTMAP optimization using hierarchical parallel genetic algorithms by Loo, C.K., Liew, W.S., Seera, M., Lim, Einly

    Published 2015
    “…To further augment the ARTMAP's pattern classification ability, multiple ARTMAPs were optimized via genetic algorithm and assembled into a classifier ensemble. …”
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  9. 9

    Analyzing RNA-Seq gene expression data using deep learning approaches for cancer classification by Laiqa Rukhsar, Waqas Haider Bangyal, Muhammad Sadiq Ali Khan, Ag Asri Ag Ibrahim, Kashif Nisar, Danda B. Rawat

    Published 2022
    “…In the next step, relevant features are extracted and selected using Deep Learning (DL). In the last phase, classification is performed, and eight DL algorithms are used. …”
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    Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition by Leong, Shi Xiang

    Published 2017
    “…There are two general paradigms for pattern recognition classification which are supervised and unsupervised learning. …”
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    Thesis
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    Enhancement of text representation for Indonesian document summarization with deep sequential pattern mining by Dian Sa’adillah Maylawati

    Published 2023
    “…Therefore, the present study aims: (1) to improve Indonesian text summary by enhancing the Sequence of Word (SoW) as text representation using Sequential Pattern Mining (SPM) with PrefixSpan algorithm since the effectiveness of SPM in Indonesian is proven useful for text classification and clustering; (2) to combine SPM and Deep Learning (DeepSPM) in text summarization with Indonesian text, as a result of its superior accuracy when trained with large amounts of data; and (3) to evaluate the readability of Indonesian text summary with several evaluation scenarios. …”
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    Thesis
  13. 13

    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
  14. 14

    Ensemble learning using multi-objective optimisation for arabic handwritten words by Ghadhban, Haitham Qutaiba

    Published 2021
    “…Future work may consider introducing more features to the system, applying them to other languages, and integrating it with sequence learning for more accuracy.…”
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    Thesis
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    Multilevel learning in Kohonen SOM network for classification problems by Mohd. Yusof, Norfadzila

    Published 2006
    “…Self-organizing map (SOM) is a feed-forward neural network approach that uses an unsupervised learning algorithm has shown a particular ability for solving the problem of classification in pattern recognition. …”
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    Thesis
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    Individual And Ensemble Pattern Classification Models Using Enhanced Fuzzy Min-Max Neural Networks by F. M., Mohammed

    Published 2014
    “…Pattern classification is one of the major components for the design and development of a computerized pattern recognition system. …”
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    Thesis
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    The Potential of a Classification-based Algorithm to Calculate Calories in Real-Time Via Pattern Recognition by M. A., Ameedeen, Marhaini, M. S.

    Published 2016
    “…While the algorithm helped to classify different types of wavelengths produced from the sensor, a classification-based algorithm via Pattern Recognition Method will be used to classify and match the food components. …”
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    Computational Technique for an Efficient Classification of Protein Sequences With Distance-Based Sequence Encoding Algorithm by Iqbal, M.J., Faye, I., Said, A.M.D., Samir, B.B.

    Published 2017
    “…The accurate classification of protein sequence would be helpful in determining the structure and function of novel protein sequences. …”
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    Article
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