Search Results - (( pattern learning algorithm ) OR ((( patterns ant algorithm ) OR ( patterns a algorithm ))))*

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  1. 1

    Lexicon-based and immune system based learning methods in Twitter sentiment analysis by Jantan, Hamidah, Drahman, Fatimatul Zahrah, Alhadi, Nazirah, Mamat, Fatimah

    Published 2016
    “…In future work, the accuracy of proposed model can be strengthened by comparative study with other heuristic based searching algorithms such as genetic algorithm, ant colony optimization, swam algorithms and etc.…”
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    Conference or Workshop Item
  2. 2

    Machine learning using robust AI techniques / Prof. Madya Dr. Nordin Abu Bakar by Abu Bakar, Nordin (Prof. Madya Dr.)

    Published 2012
    “…How does a person make a right decision ? maybe he learns from past experience or new information he receives. …”
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    Research Reports
  3. 3

    Incremental continuous ant colony optimization for tuning support vector machine’s parameters by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2013
    “…Support Vector Machines are considered to be excellent patterns classification techniques. The process of classifying a pattern with high classification accuracy counts mainly on tuning Support Vector Machine parameters which are the generalization error parameter and the kernel function parameter.Tuning these parameters is a complex process and Ant Colony Optimization can be used to overcome the difficulty. …”
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    Article
  4. 4

    Optimizing support vector machine parameters using continuous ant colony optimization by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2012
    “…Support Vector Machines are considered to be excellent patterns classification techniques.The process of classifying a pattern with high classification accuracy counts mainly on tuning Support Vector Machine parameters which are the generalization error parameter and the kernel function parameter.Tuning these parameters is a complex process and may be done experimentally through time consuming human experience.To overcome this difficulty, an approach such as Ant Colony Optimization can tune Support Vector Machine parameters.Ant Colony Optimization originally deals with discrete optimization problems. …”
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    Conference or Workshop Item
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    Ant system-based feature set partitioning algorithm for classifier ensemble construction by Abdullah, , Ku-Mahamud, Ku Ruhana

    Published 2016
    “…Ensemble method is considered as a new direction in pattern classification. Accuracy and diversity in a set of classifiers are two important things to be considered in constructing classifier ensemble.Several approaches have been proposed to construct the classifier ensemble. …”
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    Article
  7. 7

    Bat Algorithm for Complex Event Pattern Detection in Sentiment Analysis by Kabir Ahmad, Farzana, Kamaruddin, Siti Sakira, Yusof, Yuhanis, Yusoff, Nooraini

    Published 2021
    “…Thus, this study proposed a Bat Algorithm (BA) to address the complex learning structure of DBN in detecting sentiment patterns. …”
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    Monograph
  8. 8

    Big data clustering using grid computing and ant-based algorithm by Ku-Mahamud, Ku Ruhana

    Published 2013
    “…This paper presents a framework for big data clustering which utilizes grid technology and ant-based algorithm.…”
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  9. 9

    An algorithm for Elliott Waves pattern detection by Vantuch, T., Zelinka, I., Vasant, P.

    Published 2018
    “…The Random Decision Forest and the Support Vector Machine are the machine learning algorithms employed for this task. The accuracy of trend prediction above 70 proves the relevancy of EW patterns on stock market data as well as the validity of the algorithm as a tool for detection of such patterns. …”
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    Article
  10. 10

    An algorithm for Elliott Waves pattern detection by Vantuch, T., Zelinka, I., Vasant, P.

    Published 2018
    “…The Random Decision Forest and the Support Vector Machine are the machine learning algorithms employed for this task. The accuracy of trend prediction above 70 proves the relevancy of EW patterns on stock market data as well as the validity of the algorithm as a tool for detection of such patterns. …”
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    Article
  11. 11

    Ant colony algorithm for text classification in multicore-multithread environment / Ahmad Nazmi Fadzal by Fadzal, Ahmad Nazmi

    Published 2017
    “…Pheromone concept is the main criterion that distinguish ACO to other algorithms. Based on the concept, pheromone saturation is used to combine stackable solution pattern that is discovered while straying to different term node to build a path. …”
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    Thesis
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  13. 13

    Hybrid ACO and SVM algorithm for pattern classification by Alwan, Hiba Basim

    Published 2013
    “…Ant Colony Optimization (ACO) is a metaheuristic algorithm that can be used to solve a variety of combinatorial optimization problems. …”
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    Thesis
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    Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition by Leong, Shi Xiang

    Published 2017
    “…There are two general paradigms for pattern recognition classification which are supervised and unsupervised learning. …”
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    Thesis
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    Hybrid ant colony system algorithm for static and dynamic job scheduling in grid computing by Alobaedy, Mustafa Muwafak Theab

    Published 2015
    “…The proposed algorithms were evaluated against twelve metaheuristic algorithms in static (expected time to compute model) and dynamic (distribution pattern) grid computing environments. …”
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    Thesis
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    Traditional marble game using ant colony optimization / Muhammad Izzat Imran Che Isa by Che Isa, Muhammad Izzat Imran

    Published 2017
    “…The shortest distance is defined as best result. A set of data contains position of marbles is tested for ACO algorithm in the prototype. …”
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    Thesis
  19. 19

    An improved ACS algorithm for data clustering by Mohammed Jabbar, Ayad, Ku-Mahamud, Ku Ruhana, Sagban, Rafid

    Published 2020
    “…Data clustering techniques minimise intra-cluster similarity in each cluster and maximise inter-cluster dissimilarity amongst different clusters. Ant colony optimisation for clustering (ACOC) is a swarm algorithm inspired by the foraging behaviour of ants. …”
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    Article
  20. 20

    Clustering ensemble learning method based on incremental genetic algorithms by Ghaemi, Reza

    Published 2012
    “…In the first and second phases, a threshold fuzzy c-means clustering algorithm as a clusterer and a pattern ensemble learning method based on the incremental genetic-based algorithms are proposed respectively. …”
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    Thesis