Search Results - (( data classification methods algorithm ) OR ( data classification modified algorithm ))

Refine Results
  1. 1

    A novel hybrid classification model of genetic algorithms, modified k-Nearest Neighbor and developed backpropagation neural network by Salari, Nader, Shohaimi, Shamarina, Najafi, Farid, Nallappan, Meenakshii, Karishnarajah, Isthrinayagy

    Published 2014
    “…Among numerous artificial intelligence approaches, k-Nearest Neighbor algorithms, genetic algorithms, and artificial neural networks are considered as the most common and effective methods in classification problems in numerous studies. …”
    Get full text
    Get full text
    Get full text
    Article
  2. 2

    A modified weighted support vector machine (WSVM) to reduce noise data in classification problem by Mohd Dzulkifli, Syarizul Amri

    Published 2021
    “…Nowadays, the use of SVM is very perspective for the big data classification. SVM provides a global solution for data classification but SVM is highly sensitive to noise data and may not be effective when the level of noise data is high. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
  3. 3

    A modified weighted support vector machine (WSVM) to reduce noise data in classification problem by Mohd Dzulkifli, Syarizul Amri

    Published 2021
    “…Nowadays, the use of SVM is very perspective for the big data classification. SVM provides a global solution for data classification but SVM is highly sensitive to noise data and may not be effective when the level of noise data is high. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
  4. 4

    Mutable composite firefly algorithm for gene selection in microarray based cancer classification by Fajila, Mohamed Nisper Fathima

    Published 2022
    “…Evaluation was performed based on two metrics: classification accuracy and size of feature set. The results showed that the CFS-MCFA-SVM algorithm outperforms benchmark methods in terms of classification accuracy and genes subset size. …”
    Get full text
    Get full text
    Thesis
  5. 5

    Logistic regression methods for classification of imbalanced data sets by Santi Puteri Rahayu, -

    Published 2012
    “…Thus, both proposed imbalanced LR-based methods is simple and effective for classification of imbalanced data sets and have promising results.…”
    Get full text
    Get full text
    Thesis
  6. 6

    Predicting Customer Buying Decisions for Online Shopping with Unbalanced Data Set by Yap, Chau Tean

    Published 2022
    “…Six machine learning algorithms were applied and compared based on the classification evaluation methods. …”
    Get full text
    Get full text
    Final Year Project / Dissertation / Thesis
  7. 7

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

    An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

    Published 2015
    “…Major problems in classification task are large amount of training data, large number of features and different behavior of data streams that reduce accuracy and increase computational cost in classifier training phase. …”
    Get full text
    Get full text
    Thesis
  9. 9

    Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification by Myaser, Jwan

    Published 2020
    “…The last phase involves developing a new fusion algorithm using SVM and Fuzzy K-Means Clustering (FKM) algorithms for Sentinel 2 data to enhance LCM accuracy. …”
    Get full text
    Get full text
    Thesis
  10. 10
  11. 11

    Identifying diseases and diagnosis using machine learning by Iswanto I., Laxmi Lydia E., Shankar K., Nguyen P.T., Hashim W., Maseleno A.

    Published 2023
    “…For classify the disease classification algorithms are used. It uses are many dimensionality reduction algorithms and classification algorithms. …”
    Article
  12. 12

    Enhanced Image Classification for Defect Detection on Solar Photovoltaic Modules by Wiliani, Ninuk

    Published 2023
    “…The second algorithm uses K Nearest Neighbour using a ratio of training data and testing data of 95:05 resulting in an accuracy value of 62%. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
  13. 13

    Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals by Too, Jing Wei

    Published 2020
    “…The second method is called the Modified Binary Tree Growth Algorithm (MBTGA) that applies swap, crossover, and mutation operators. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
  14. 14

    Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi by Atefi, Kayvan

    Published 2019
    “…Experiments demonstrate and prove that the proposed EBPSO method produces better accuracy mining data and selecting subset of relevant features comparing other algorithms. …”
    Get full text
    Get full text
    Thesis
  15. 15

    Robust diagnostics and variable selection procedure based on modified reweighted fast consistent and high breakdown estimator for high dimensional data by Baba, Ishaq Abdullahi

    Published 2022
    “…In addressing this problem, some robust procedures for high dimensional dataset via the RFCH algorithm are developed. A modified reweighted fast consistent and high breakdown (MRFCH) estimator in high dimensional data based on the diagonal elements of the scatter matrix instead of its entire elements in the computation of robust Mahalanobis distance within the RFCH algorithm is developed. …”
    Get full text
    Get full text
    Thesis
  16. 16

    Analysis of multicomponent transient signals using music superresolution technique by Jibia, Abdussamad Umar, Salami, Momoh Jimoh Emiyoka, Khalifa, Othman Omran

    Published 2008
    “…Many techniques have been suggested by researchers to analyse these signals but they often produce mixed results. A new method of analysis using modified MUSIC (multiple signal classification) subspace algorithm is successfully applied to the analysis of this signal. …”
    Get full text
    Get full text
    Proceeding Paper
  17. 17

    Feature fusion using a modified genetic algorithm for face and signature recognition system by Suryanti, Awang

    Published 2015
    “…Several approaches and benchmark data were used to validate the effectiveness of the proposed method compared to the unimodal system and normal feature selection method. …”
    Get full text
    Get full text
    Thesis
  18. 18

    Integrated artificial intelligence-based classification approach for prediction of acute coronary syndrome by Salari, Nader

    Published 2014
    “…The classification performance of K1-K2-NN model was benchmarked against 13 commonly used classification models using repeated random sub-sampling crossvalidation on ACSEKI data set. …”
    Get full text
    Get full text
    Get full text
    Thesis
  19. 19

    Electroencephalogram-based decoding cognitive states using convolutional neural network and likelihood ratio based score fusion by Zafar, R., Dass, S.C., Malik, A.S.

    Published 2017
    “…Comprehensive analysis was conducted using data from 30 participants. The results from the proposed method are compared with current recognized feature extraction and classification/prediction techniques. …”
    Get full text
    Get full text
    Article
  20. 20

    Improving Support Vector Machine Performance using Modified Similarity Distance Plotting-Data Reduction by Abdul Muqtasid, Rushdi, Mohammad, Hossin, Norita, Norwawi

    Published 2025
    “…To address this, we introduce the Similarity Distance Plotting-Data Reduction (SDP-DR) method, a novel instance selection technique aimed at enhancing SVM's efficiency and generalization. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Article