Search Results - (( feature classification methods algorithm ) OR ( variable optimization method algorithm ))

Refine Results
  1. 1
  2. 2

    A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification by Talpur, N., Abdulkadir, S.J., Hasan, M.H., Alhussian, H., Alwadain, A.

    Published 2023
    “…The performance of the proposed SCSO algorithm was compared with six state-of-the-art and recent wrapper-based optimization algorithms using the validation metrics of classification accuracy, optimum feature size, and computational cost in seconds. …”
    Get full text
    Get full text
    Article
  3. 3

    Intelligent classification algorithms in enhancing the performance of support vector machine by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2019
    “…This paper presents two intelligent algorithms that hybridized between ant colony optimization (ACO) and SVM for tuning SVM parameters and selecting feature subset without having to discretize the continuous values. …”
    Get full text
    Get full text
    Get full text
    Article
  4. 4

    An evolutionary based features construction methods for data summarization approach by Rayner Alfred, Suraya Alias, Chin, Kim On

    Published 2015
    “…Here, feature construction methods are applied in order to improve the descriptive accuracy of the DARA algorithm.This research proposes novel feature construction methods, called Variable Length Feature Construction without Substitution (VLFCWOS) and Variable Length Feature Construction with Substitution(VLFCWS), in order to construct a set of relevant features in learning relational data. …”
    Get full text
    Get full text
    Research Report
  5. 5

    Improvement on rooftop classification of worldview-3 imagery using object-based image analysis by Norman, Masayu

    Published 2019
    “…Furthermore, a systematic feature selection approach was proposed in which search algorithms (Ant-Search, Best First-Search and Particle Swamp Optimization (PSO) - Search) performance were evaluated to select the most significant features. …”
    Get full text
    Get full text
    Thesis
  6. 6

    Information Theoretic-based Feature Selection for Machine Learning by Muhammad Aliyu, Sulaiman

    Published 2018
    “…In these extended IFS method, feature selection method was defined and presented as a 0-1 Knapsack Problem (MKP). …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
  7. 7

    Optimal Weighted Learning of PCA and PLS for Multicollinearity Discriminators and Imbalanced Groups in Big Data (S/O: 13224) by Mahat, Nor Idayu, Engku Abu Bakar, Engku Muhammad Nazri, Zakaria, Ammar, Mohd Nazir, Mohd Amril Nurman, Misiran, Masnita

    “…The designed algorithm was structured in k-fold cross-validation in attempt to minimise the biasness of the classification performance, measured using error rate. …”
    Get full text
    Get full text
    Monograph
  8. 8

    A genetic algorithm based fuzzy inference system for pattern classification and rule extraction by Wong S.Y., Yap K.S., Li X.

    Published 2023
    “…Therefore, our proposed GA-FIS method will first define the membership functions with logical interpretation which is amendable by domain experts to human understanding, and then genetic algorithm serves as an optimization tool to construct the best combination of rules in fuzzy inference system that can achieve higher classification accuracy and gain better interpretability. …”
    Article
  9. 9

    Liver segmentation on CT images using random walkers and fuzzy c-means for treatment planning and monitoring of tumors in liver cancer patients by Moghbel, Mehrdad

    Published 2017
    “…This is followed by the clustering of the liver tissues using particle swarm optimized spatial FCM algorithm. Then, these tissues are classified into tumors and blood vessels by an AdaBoost classification method based on tissue features extracted utilizing first, second and higher order image features selected by a minimal-redundancy maximalrelevance feature selection approach. …”
    Get full text
    Get full text
    Get full text
    Thesis
  10. 10

    Statistical band selection for descriptors of MBSE and MFCC-based features for accent classification of Malaysian English / Yusnita M. A. ...[et al.] by M. A., Yusnita, M. P., Paulraj, Yaacob, Sazali, A. B., Shahriman, Mokhtar, Nor Fadzilah

    Published 2013
    “…This paper proposes an efficient way of analyzing the ethnical accent using statistical knowledge of log-energies of fourier transformed derived mel-filter banks. A simple algorithm to select bands so called statistical band selection (SBS) method using smallest variances within class scores was developed to optimize the presentation of speech features. …”
    Get full text
    Get full text
    Get full text
    Article
  11. 11

    Feature Ranking Techniques For 3D ATS Drug Molecular Structure Identification by Saw, Yee Ching

    Published 2018
    “…The results show that the feature subset selected by the FEFR feature selection approach is either superior or at least as adequate as those subsets that selected by the individual feature ranking method and the original dataset.…”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
  12. 12

    Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

    Published 2004
    “…All these approaches are implemented with RELIEF feature selection approach. The classification accuracy obtained from the CST method is compared to other selected classification methods such as Value Difference Metric (VDM), Pre-Category Feature Importance (PCF), Cross-Category Feature Importance (CCF), Instance-Based Algorithm (IB4), Decision Tree Algorithms such as Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5), Rough Set methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) and Neural Network methods such as the Multilayer method.…”
    Get full text
    Get full text
    Thesis
  13. 13

    Utilizing artificial bee colony algorithm as feature selection method in Arabic text classification by Hijazi, Musab, Zeki, Akram M., Ismail, Amelia Ritahani

    Published 2023
    “…One of the widely used algorithms for feature selection in text classification is the Evolutionary algorithm . …”
    Get full text
    Get full text
    Get full text
    Get full text
    Article
  14. 14

    Aco-based feature selection algorithm for classification by Al-mazini, Hassan Fouad Abbas

    Published 2022
    “…The modified graph clustering ant colony optimisation (MGCACO) algorithm is an effective FS method that was developed based on grouping the highly correlated features. …”
    Get full text
    Get full text
    Thesis
  15. 15

    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
    “…Third, using a modified k-Nearest Neighbor method as well as an improved method of backpropagation neural networks, the classification process was advanced based on optimum arrays of the features selected by genetic algorithms. …”
    Get full text
    Get full text
    Get full text
    Article
  16. 16

    Development of a fingerprint gender classification algorithm using fingerprint global features by Abdullah, Siti Fairuz, Abdul Rahman, Ahmad Fadzli Nizam, Abal Abas, Zuraida, Mohd Saad, Wira Hidayat

    Published 2016
    “…This study is meant to enhance the forensic manual method by proposing a new algorithm for fingerprint global feature extraction for gender classification. …”
    Get full text
    Get full text
    Get full text
    Article
  17. 17

    Arabic text classification using hybrid feature selection method using chi-square binary artificial bee colony algorithm by Hijazi, Musab, Zeki, Akram M., Ismail, Amelia Ritahani

    Published 2021
    “…Furthermore, the proposed method had a better performance compared with the chi-square method and the ABC algorithm as a feature selection method…”
    Get full text
    Get full text
    Get full text
    Get full text
    Get full text
    Article
  18. 18

    Ideal combination feature selection model for classification problem based on bio-inspired approach by Basir, Mohammad Aizat, Hussin, Mohamed Saifullah, Yusof, Yuhanis

    Published 2020
    “…The important step is to idealize the combined feature selection models by finding the best combination of search method and feature selection algorithms. …”
    Get full text
    Get full text
    Book Section
  19. 19

    Realization Of The 1D Local Binary Pattern (LBP) Algorithm In Raspberry Pi For Iris Classification Using K-NN Classifier by Siow, Shien Loong

    Published 2018
    “…Due to the current methods in feature extraction are still improving, this project proposed a new feature extraction method to increase the performance of iris classification. …”
    Get full text
    Get full text
    Monograph
  20. 20

    Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms by Rachmad, Iqbal, Tri Basuki, Kurniawan, Misinem, ., Edi Surya, Negara, Tata, Sutabri

    Published 2024
    “…This research compares three different methods for extracting features from fruit images to determine which method yields the highest accuracy for fruit classification. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Article