Search Results - (( code classifications clustering algorithm ) OR ( based classification problems algorithm ))

Search alternatives:

Refine Results
  1. 1
    Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning

    Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning by Safa, Soodabeh

    Published 2016
    “…Beside that, classic bag of visual words algorithm (BoVW) is based on kmeans clustering and every SIFT feature belongs to one cluster and it leads to decreasing classification results. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  2. 2
    Automatic detection and indication of pallet-level tagging from rfid readings using machine learning algorithms

    Automatic detection and indication of pallet-level tagging from rfid readings using machine learning algorithms by Choong, Chun Sern

    Published 2020
    “…The ensemble learning technique, changes of activation function in Neural Network as well as the unsupervised learning (k-means clustering algorithm and Friis Transmission Equation) was also applied to classify the multiclass classification in pallet-level. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  3. 3
    An improved plant identification system by Fuzzy c-means bag of visual words model and sparse coding

    An improved plant identification system by Fuzzy c-means bag of visual words model and sparse coding by Safa, Soodabeh, Khalid, Fatimah

    Published 2020
    “…Classic bag of visual words algorithm is based on k-means clustering and every SIFT features belongs to one cluster and it leads to decreasing classification results. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  4. 4
    An adaptive ant colony optimization algorithm for rule-based classification

    An adaptive ant colony optimization algorithm for rule-based classification by Al-Behadili, Hayder Naser Khraibet

    Published 2020
    “…The algorithm’s performance was compared with other variants of Ant-Miner and state-of-the-art rules-based classification algorithms based on classification accuracy and model complexity. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  5. 5
    Classification of metamorphic virus using n-grams signatures

    Classification of metamorphic virus using n-grams signatures by A Hamid, Isredza Rahmi, Md Sani, Nur Sakinah, Abdullah, Zubaile, Mohd Foozy, Cik Feresa, Kipli, Kuryati

    Published 2020
    “…The first step is the classification model to cluster the metamorphic virus using TF-IDF technique. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  6. 6
    Classification for large number of variables with two imbalanced groups

    Classification for large number of variables with two imbalanced groups by Ahmad Hakiim, Jamaluddin

    Published 2020
    “…This study proposed two algorithms of classification namely Algorithm 1 and Algorithm 2 which combine resampling, variable extraction, and classification procedure. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  7. 7
    Dengue classification system using clonal selection algorithm / Karimah Mohd

    Dengue classification system using clonal selection algorithm / Karimah Mohd by Mohd, Karimah

    Published 2012
    “…This project can be improved by making a comparative study on Artificial Immune System and other techniques or algorithms used to solve dengue classification problems.…”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  8. 8
    Mutable composite firefly algorithm for gene selection in microarray based cancer classification

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

    Published 2022
    “…A computational approach for gene selection based on microarray data analysis has been applied in many cancer classification problems. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  9. 9
    WCBP: A new water cycle based back propagation algorithm for data classification

    WCBP: A new water cycle based back propagation algorithm for data classification by Mohd. Nawi, Nazri, Khan, Abdullah, Firdaus, Naim, M. Z., Rehman, Siming, Insaf Ali

    Published 2016
    “…The performance of the proposed Water Cycle based Back-Propagation (WCBP) algorithm is compared with the conventional BPNN, ABC-BP and ABC-LM algorithms on selected benchmark classification problems from UCI Machine Learning Repository. …”
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  10. 10
    Formulating new enhanced pattern classification algorithms based on ACO-SVM

    Formulating new enhanced pattern classification algorithms based on ACO-SVM by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2013
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  11. 11
    Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd

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

    Published 2022
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  12. 12
    Overview of metaheuristic: classification of population and trajectory

    Overview of metaheuristic: classification of population and trajectory by Zainul Rashid, Zarina

    Published 2010
    “…One of the classifications is population vs. trajectory. In this paper, several algorithm techniques based on population and trajectory characteristics are discussed. …”
    Get full text
    Get full text
    Monograph
    Save to List
    Saved in:
  13. 13
    A derivative-free optimization method for solving classification problem

    A derivative-free optimization method for solving classification problem by Shabanzadeh, Parvaneh, Abu Hassan, Malik, Leong, Wah June

    Published 2010
    “…The results of numerical experiments allowed us to say the proposed algorithms are effective for solving classification problems at least for databases considered in this study.…”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  14. 14
    Enhancing teaching and learning through data-driven optimization of servicing code demand and lecturer allocation using WEKA analysis

    Enhancing teaching and learning through data-driven optimization of servicing code demand and lecturer allocation using WEKA analysis by Rochin Demong, Nur Atiqah, Mohamed Razali, Murni Zarina, Kamaruddin, Juliana Noor, Shamsuddin, Sazwan, Awang, Nor Ain, Kamarudin, Norjuliatie, Wan Othman, Noor Faradilla

    Published 2025
    “…Furthermore, classification using the Random Forest algorithm depicted that a 95.3% accuracy (k=0.768), confirming robust predictive capability in identifying course approval status and demand trends. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  15. 15
    Grid-Based Classifier as a Replacement for Multiclass Classifier in a Supervised Non-Parametric Approach

    Grid-Based Classifier as a Replacement for Multiclass Classifier in a Supervised Non-Parametric Approach by Moheb Pour, Majid Reza

    Published 2009
    “…In the current research, the new algorithm was tested and applied to the multiclass classification of two or more categories, which are important for handling problems related to practical classification. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  16. 16
    Grid base classifier in comparison to nonparametric methods in multiclass classification

    Grid base classifier in comparison to nonparametric methods in multiclass classification by Moheb Pour, Majid Reza, Jantan, Adznan, Saripan, M. Iqbal

    Published 2010
    “…In the current research, the new algorithm was tested and applied to the multiclass classification of two or more categories, which are important for handling problems related to practical classification. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  17. 17
    Logistic regression methods for classification of imbalanced data sets

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

    Published 2012
    “…The imbalanced problem of both proposed general classification algorithms which is the limitation of accuracy performance specifically in classifying on the minority class has motivated this research to improve their classification performance on imbalanced data sets. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  18. 18
    Enhancement of bearing defect diagnosis via genetic algorithm optimized feature selection

    Enhancement of bearing defect diagnosis via genetic algorithm optimized feature selection by Chia, Yee Shin

    Published 2015
    “…Subsequently, the integration of embedded correlation-based filtering algorithm has further increased the classification accuracy of training process and testing process by 4.93% and 14.73% respectively. …”
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  19. 19
    Rule pruning techniques in the ant-miner classification algorithm and its variants: A review

    Rule pruning techniques in the ant-miner classification algorithm and its variants: A review by Al-Behadili, Hayder Naser Khraibet, Ku-Mahamud, Ku Ruhana, Sagban, Rafid

    Published 2018
    “…Rule-based classification is considered an important task of data classification.The ant-mining rule-based classification algorithm, inspired from the ant colony optimization algorithm, shows a comparable performance and outperforms in some application domains to the existing methods in the literature.One problem that often arises in any rule-based classification is the overfitting problem. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  20. 20
    Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model

    Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model by Sulaiman, Md. Nasir, Mohamed, Raihani, Mustapha, Norwati, Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…Meanwhile, Kmeans clustering algorithm has also been reported has widely known for solving most unsupervised classification problems. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:

Search Tools: