Search Results - (( mining classification issues algorithm ) OR ( using optimization based algorithm ))

Refine Results
  1. 1

    Improvement of fuzzy neural network using mine blast algorithm for classification of Malaysian Small Medium Enterprises based on strength by Hussain Talpur, Kashif

    Published 2015
    “…Many researchers have trained ANFIS parameters using metaheuristic algorithms but very few have considered optimizing the ANFIS rule-base. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
  2. 2

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

    Published 2019
    “…Despite attempts to solve the data clustering issues, there are also many variants of modified algorithms in traditional information clustering that attempt to solve issues such as clustering algorithms based on condensation. …”
    Get full text
    Get full text
    Thesis
  3. 3

    Feature Subset Selection in Intrusion Detection Using Soft Computing Techniques by AHMAD, IFTIKHAR

    Published 2011
    “…Based on the selected features, the classification is performed. …”
    Get full text
    Get full text
    Thesis
  4. 4

    Towards a better feature subset selection approach by Shiba, Omar A. A.

    Published 2010
    “…The selection of the optimal features subset and the classification has become an important issue in the data mining field.We propose a feature selection scheme based on slicing technique which was originally proposed for programming languages.The proposed approach called Case Slicing Technique (CST).Slicing means that we are interested in automatically obtaining that portion 'features' of the case responsible for specific parts of the solution of the case at hand.We show that our goal should be to eliminate the number of features by removing irrelevant once.Choosing a subset of the features may increase accuracy and reduce complexity of the acquired knowledge.Our experimental results indicate that the performance of CST as a method of feature subset selection is better than the performance of the other approaches which are RELIEF with Base Learning Algorithm (C4.5), RELIEF with K-Nearest Neighbour (K-NN), RELIEF with Induction of Decision Tree Algorithm (ID3) and RELIEF with Naïve Bayes (NB), which are mostly used in the feature selection task.…”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  5. 5

    Feature Subset Selection in Intrusion Detection Using Soft Computing Techniques by Iftikhar , Ahmad, Azween, Abdullah

    Published 2011
    “…Based on the selected features, the classification is performed. …”
    Get full text
    Get full text
    Thesis
  6. 6

    An enhancement of classification technique based on rough set theory for intrusion detection system application by Noor Suhana, Sulaiman

    Published 2019
    “…Thus, to deal with huge dataset, data mining technique can be improved by introducing discretization algorithm to increase classification performance. …”
    Get full text
    Get full text
    Thesis
  7. 7

    Talent classification using support vector machine technique / Hamidah Jantan, Norazmah Mat Yusof and Mohd Hanapi Abdul Latif by Jantan, Hamidah, Mat Yusof, Norazmah, Abdul Latif, Mohd Hanapi

    Published 2014
    “…Support Vector Machine (SVM) is among the popular learning algorithm for classification in soft computing techniques. …”
    Get full text
    Get full text
    Research Reports
  8. 8
  9. 9

    Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining. by Saeed, Walid

    Published 2005
    “…Therefore generating a good decision model or classification model is a major component in many data mining researches. …”
    Get full text
    Get full text
    Thesis
  10. 10

    Intuitive Content Management System to Preferences Template Throughout Data Collection by using Data Mining Classification of Prediction Method by Chan, Chung Hoong, M. A., Ameedeen

    Published 2016
    “…The sophisticated mathematical algorithm applies in data mining to segment data and evaluates the probability of a future event. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  11. 11

    Building classification models from imbalanced fraud detection data / Terence Yong Koon Beh, Swee Chuan Tan and Hwee Theng Yeo by Terence, Yong Koon Beh, Swee, Chuan Tan, Hwee, Theng Yeo

    Published 2014
    “…We evaluated the models generated from seven classification algorithms with two simple data balancing techniques. …”
    Get full text
    Get full text
    Get full text
    Article
  12. 12
  13. 13
  14. 14

    Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets by Saeed, Sana

    Published 2019
    “…Classification of imbalanced datasets remained a significant issue in data mining and machine learning (ML) fields. …”
    Get full text
    Get full text
    Thesis
  15. 15

    Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd by Nur Farahaina, Idris

    Published 2022
    “…The study verified that the FID3-DBD algorithm could classify the continuous data, and the BFID3-DBD algorithm overcame the overfitting issue, reduced high variance, and increased test data classification accuracy.…”
    Get full text
    Get full text
    Thesis
  16. 16
  17. 17
  18. 18

    A Predictive Classification Model For Running Injury by Ganesan, Devesh Raj

    Published 2022
    “…The J48, SMO, Random Forest, and Simple Logistic algorithms were used for 10-fold cross validation mode classification benchmarked on the ZeroR baseline algorithm. …”
    Get full text
    Get full text
    Monograph
  19. 19

    AN AGENT-BASED DOCUMENT CLASSIFICATION MODEL TO IMPROVE THE EFFICIENCY OF THE AUTOMATED SYSTEMATIC REVIEW PROCESS by Khashfeh M., Mahmoud M.A., Mahdi M.N.

    Published 2023
    “…Secondly, the multi-agent architecture accelerates the mining process and handles the performance issues. …”
    Review
  20. 20