Search Results - (( data optimization based algorithm ) OR ( sequence classification using algorithm ))

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  1. 1

    Optimized tree-classification algorithm for classification of protein sequences by Iqbal, M.J., Faye, I., Said, A.M., Belhaouari Samir, B.

    Published 2016
    “…In this work, we have proposed an optimized tree-classification technique which uses cluster k nearest neighbor classification algorithm to classify protein sequences into superfamilies. …”
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  2. 2

    Optimized tree-classification algorithm for classification of protein sequences by Iqbal, M.J., Faye, I., Said, A.M., Belhaouari Samir, B.

    Published 2016
    “…In this work, we have proposed an optimized tree-classification technique which uses cluster k nearest neighbor classification algorithm to classify protein sequences into superfamilies. …”
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    Conference or Workshop Item
  3. 3

    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
    “…In this article, we have proposed a distance-based sequence encoding algorithm that captures the sequence's statistical characteristics along with amino acids sequence order information. …”
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    Article
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  5. 5

    Evaluation and optimization of frequent association rule based classification by Izwan Nizal Mohd Shaharanee, Jastini Jamil

    Published 2014
    “…In this paper, a systematic way to evaluate the association rules discovered from frequent itemset mining algorithms, combining common data mining and statistical interestingness measures, and outline an appropriated sequence of usage is presented. …”
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    Article
  6. 6

    Evaluation and optimization of frequent, closed and maximal association rule based classification by Mohd Shaharanee, Izwan Nizal, Hadzic, Fedja

    Published 2014
    “…Real world applications of association rule mining have well-known problems of discovering a large number of rules, many of which are not interesting or useful for the application at hand.The algorithms for closed and maximal item sets mining significantly reduce the volume of rules discovered and complexity associated with the task, but the implications of their use and important differences with respect to the generalization power, precision and recall when used in the classification problem have not been examined.In this paper, we present a systematic evaluation of the association rules discovered from frequent, closed and maximal item set mining algorithms, combining common data mining and statistical interestingness measures, and outline an appropriate sequence of usage.The experiments are performed using a number of real-world datasets that represent diverse characteristics of data/items, and detailed evaluation of rule sets is provided as a whole and w.r.t individual classes. …”
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    Article
  7. 7

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

    Published 2012
    “…The optimal combination of λ and training sequence can be computed efficiently using a genetic permutation algorithm. …”
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  8. 8

    Angle Based Protein Tertiary Structure Prediction Using Bees Optimization Algorithm by Al-Qattan, Zakaria Noor Aldeen Mahmood

    Published 2010
    “…WEKA program application was used for main chain angles (Phi and Psi) data classification. …”
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    Thesis
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  10. 10

    Detection of Workers’ Behaviour in the Manufacturing Plant using Deep Learning by Goh, Ching Pang

    Published 2023
    “…The primary aim is to quantify human behavior based on learning rates, thereby facilitating improved production control. …”
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    Article
  11. 11

    NETASA: neural network based prediction of solvent accessibility by Ahmad, Shandar, Gromiha, M. Michael

    Published 2002
    “…In the present work, we have implemented a server, NETASA for predicting solvent accessibility of amino acids using our newly optimized neural network algorithm. …”
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    Article
  12. 12

    A study on component-based technology for development of complex bioinformatics software by Ali Shah, Zuraini, Deris, Safaai, Othman, Muhamad Razib, Zakaria, Zalmiyah, Saad, Puteh, Hassan, Rohayanti, Muda, Mohd. Hilmi, Kasim, Shahreen, Roslan, Rosfuzah

    Published 2004
    “…The second layer uses discriminative SVM algorithm with a state-of-the-art string kernel based on PSI-BLAST profiles that is used to leverage the unlabeled data. …”
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    Monograph
  13. 13

    Content adaptive fast motion estimation based on spatio-temporal homogeneity analysis and motion classification by Nisar, Humaira, Malik, Aamir Saeed, Choi, Tae-Sun

    Published 2012
    “…This is the basis of the proposed algorithm. The proposed algorithm involves a multistage approach that includes motion vector prediction and motion classification using the characteristics of video sequences. …”
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    Article
  14. 14

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

    Published 2021
    “…Evaluation metrics from two perspectives classification and Multiobjective optimization. The experimental design based on two subsets of the IFN/ENIT database. …”
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    Thesis
  15. 15

    Protein Sequences Classification Using Modular RBF Neural Networks by Wang, Dianhui, Lee, Nung Kion, Dillon, Tharam S., Hoogenraad, Nicholas J.

    Published 2002
    “…These algorithms compare an unseen protein sequence with all the identified protein sequences and returned the higher scored protein sequences. …”
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    Book Chapter
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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
  18. 18

    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
  19. 19

    Data mining of protein sequences with amino acid position-based feature encoding technique by Iqbal, M.J., Faye, I., Md Said, A., Samir, B.B.

    Published 2014
    “…The classification results indicate that the proposed encoding technique with a decision tree classification algorithm has achieved 85.9 classification accuracy over the Yeast protein sequence dataset. …”
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    Article
  20. 20

    An efficient computational intelligence technique for classification of protein sequences by Iqbal, M.J., Faye, I., Said, A.M., Samir, B.B.

    Published 2014
    “…The accurate annotation of the unknown protein using the classification of the protein sequence into an existing superfamily is considered a critical and challenging task in bioinformatics and computational biology. …”
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    Conference or Workshop Item