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

Refine Results
  1. 1

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

    Published 2022
    “…First, to investigate the methods used to address limitations associated with microbiome-based datasets in colorectal cancer identification using deep neural network algorithms. …”
    Get full text
    Get full text
    Get full text
    Thesis
  2. 2
  3. 3

    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. …”
    Get full text
    Get full text
    Get full text
    Article
  4. 4

    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. …”
    Get full text
    Get full text
    Conference or Workshop Item
  5. 5
  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. …”
    Get full text
    Get full text
    Article
  7. 7

    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. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
  8. 8

    Prediction Of Antimicrobial Peptides Based On Sequence Alignment And Secondary Structure Sequence And Segment Sequence.pdf by Soh , Meng Wah

    Published 2015
    “…In this study, a new algorithm is proposed as a computational tool by integrating the sequence alignment method and the secondary structure sequence (SSS) and segment sequence (SS). …”
    Get full text
    Get full text
    Thesis
  9. 9

    Computational analysis of biological data: Where are we? by Soreq, Lilach, Mohamed, Wael Mohamed Yousef

    Published 2024
    “…Computer modeling allows such electrical stimulations using statistics, bioinformatics and advanced machine-learning algorithms. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Book Chapter
  10. 10

    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 performance of the proposed technique is validated using some of the best performing classifiers implemented previously for protein sequence classification. …”
    Get full text
    Get full text
    Article
  11. 11

    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. …”
    Get full text
    Get full text
    Conference or Workshop Item
  12. 12

    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. …”
    Get full text
    Get full text
    Conference or Workshop Item
  13. 13

    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. …”
    Get full text
    Get full text
    Monograph
  14. 14

    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. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Article
  15. 15

    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. …”
    Get full text
    Get full text
    Get full text
    Article
  16. 16

    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. …”
    Get full text
    Get full text
    Get full text
    Book Chapter
  17. 17
  18. 18

    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. …”
    Get full text
    Get full text
    Get full text
    Article
  19. 19

    A collision resistant cryptographic hash function based on cellular automata rules by Jamil, Norziana

    Published 2013
    “…The 3000 sequences of 256-bit hash values are tested for randomness using NIST Statistical Tests and the results show that the output values from STITCH-256 for these sequences are random. …”
    Get full text
    Get full text
    Thesis
  20. 20

    A fuzzy approach for early human action detection / Ekta Vats by Ekta, Vats

    Published 2016
    “…There exists well-known classifiers such as Support Vector Machines (SVM), K-nearest Neighbour (KNN), etc. to perform action classification. However, the employability of these algorithms depends on the desired application and its requirements. …”
    Get full text
    Get full text
    Thesis