Search Results - (( data classification using algorithm ) OR ( problem representation using algorithm ))

Refine Results
  1. 1
  2. 2

    Sentiment analysis for malay newspaper (SAMNews) using negative selection algorithm / Nur Amalina Redzuan by Redzuan, Nur Amalina

    Published 2013
    “…While in Experiment III used 900 newspaper’s sentences as the training data and 100 newspaper’s sentences as the testing data and the accuracy is unproved to 65.81%. …”
    Get full text
    Get full text
    Thesis
  3. 3

    The importance of data classification using machine learning methods in microarray data by Jaber, Aws Naser, Moorthy, Kohbalan, Machap, Logenthiran, Safaai, Deris

    Published 2021
    “…One of these challenges involves high dimensional data that are redundant, irrelevant, and noisy. To alleviate this problem, this representation should be simplified. …”
    Get full text
    Get full text
    Get full text
    Article
  4. 4

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

    Published 2018
    “…Hitherto, the majority of computer vision approaches have been focused on designing sophisticated algorithms to achieve a robust feature representation for plant data. …”
    Get full text
    Get full text
    Get full text
    Thesis
  5. 5

    Automatic identification of epileptic seizures from EEG signals using sparse representation-based classification by Sobhan Sheykhivand, Tohid Yousefi Rezaii, Zohreh Mousavi, Azra Delpak, Ali Farzamnia

    Published 2020
    “…This study is based on sparse representation-based classification (SRC) theory and the proposed dictionary learning using electroencephalogram (EEG) signals. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Get full text
    Article
  6. 6

    k-nearest neighbour using ensemble clustering based on feature selection approach to learning relational data by Alfred, Rayner, Shin, Kung Ke, Sainin, Mohd Shamrie, On, Chin Kim, Pandiyan, Paulraj Murugesa, Ag Ibrahim, Ag Asri

    Published 2016
    “…Due to the growing amount of data generated and stored in relational databases, relational learning has attracted the interest of researchers in recent years.Many approaches have been developed in order to learn relational data.One of the approaches used to learn relational data is Dynamic Aggregation of Relational Attributes (DARA).The DARA algorithm is designed to summarize relational data with one-to-many relations. …”
    Get full text
    Get full text
    Book Section
  7. 7
  8. 8

    Pendiskretan data set kasar menggunakan ta’akulan boolean by Rokiah @ Rozita Ahmad, Maslina Darus, Siti Mariyam Shamsuddin, Azuraliza Abu Bakar

    Published 2004
    “…Emphirical results showed that the quality of the classification depends on the discretization algorithm used in the input data pre-processing phase. …”
    Get full text
    Get full text
    Get full text
    Article
  9. 9

    A review: radar-based fall detection sensor / Hidayatusherlina Razali ... [et al.] by Razali, Hidayatusherlina, Abd. Rashid, Nur Emileen, Nasarudin, Muhammad Nazrin Farhan, Ismail, Nor Najwa, Ismail Khan, Zuhani, Enche Ab Rahim, Siti Amalina

    Published 2024
    “…Fall recognition involves steps: sensor type, data pre-processing, and data classification. This study examines radar's use in fall detection and how fall detection systems can enhance people's lives.…”
    Get full text
    Get full text
    Article
  10. 10
  11. 11

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

    Published 2004
    “…The RSNN provides a novel methodology for designing nonlinear filters without prior knowledge of the problem domain. The RNN was used to detect patterns present in satellite image. …”
    Get full text
    Get full text
    Thesis
  12. 12

    Edge assisted crime prediction and evaluation framework for machine learning algorithms by Adhikary, Apurba, Murad, Saydul Akbar, Munir, Md Shirajum, Choong Seon, Hong Seong

    Published 2022
    “…Criminal risk is predicted using classification models for a particular time interval and place. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  13. 13

    Data fusion and multiple classifier systems for human activity detection and health monitoring: Review and open research directions by Nweke, Henry Friday, Teh, Ying Wah, Mujtaba, Ghulam, Al-Garadi, Mohammed Ali

    Published 2019
    “…These sensors are pre-processed and different feature sets such as time domain, frequency domain, wavelet transform are extracted and transform using machine learning algorithm for human activity classification and monitoring. …”
    Get full text
    Get full text
    Article
  14. 14

    Localized deep extreme learning machines for efficient RGB-D object recognition by Mohd Zaki, Hasan Firdaus, Shafait, Faisal, Mian, Ajmal S.

    Published 2015
    “…In this paper, we propose Localized Deep Extreme Learning Machines (LDELM) that efficiently learn features from RGB-D data. By using localized patches, not only is the problem of data sparsity solved, but the learned features are robust to occlusions and viewpoint variations. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Proceeding Paper
  15. 15

    Wavelet-Based Fractal Analysis of rs-fMRI for Classification of Alzheimer�s Disease by Sadiq, A., Yahya, N., Tang, T.B., Hashim, H., Naseem, I.

    Published 2022
    “…As a result, the conventional correlation of rs-fMRI signals may not accurately reflect the functional dynamic of spontaneous neuronal activities. This problem can be solved by using a better representation of neuronal activities provided by the connectivity of nonfractal components. …”
    Get full text
    Get full text
    Article
  16. 16

    Spiking Neural Network For Energy Efficient Learning And Recognition by Wong, Yan Chiew, Wang, Ning Lo

    Published 2020
    “…Spiking neural networks have emerged that achieve favourable advantages in terms of energy and time efficiency by using spikes for computation and communication as well as solving different problems such as pattern classification and image processing. …”
    Get full text
    Get full text
    Get full text
    Article
  17. 17

    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. …”
    Get full text
    Get full text
    Thesis
  18. 18

    Metric's thresholds for encoding evolutionary computing representation in software engineering problem by Md Sultan, Abu Bakar, Din, Jamilah, Zulzalil, Hazura, Bakar, Abubakar Diwani

    Published 2015
    “…Algorithm was tested to metric selection problem using Genetic Algorithm and the results obtained are promising.…”
    Get full text
    Get full text
    Get full text
    Article
  19. 19

    Enhanced Adaptive Neuro-Fuzzy Inference System Classification Method for Intrusion Detection by Jia, Liu

    Published 2024
    “…However, due to the constraint of having only 5 layers, ANFIS is unable to identify higher-level and more abstract representations of the data. To address this problem, this study first uses CART (Classification and Regression Tree) to enhance the depth of ANFIS, providing a deeper and interpretable hybrid architecture. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
  20. 20

    A comparative representation approach to modern heuristic search methods in a job shop by Dominic P, Dhanapal Durai, Ahmad, Kamil, Parthiban, P, Lenny Koh, SC

    Published 2008
    “…This research article addresses the problem of static job shop scheduling on the job-based representation and the rule-based representations. …”
    Get full text
    Get full text
    Citation Index Journal