Search Results - (( using classification using algorithm ) OR ( post implementation using algorithm ))

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  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
    “…In the present study, the results of the implementation of a novel hybrid feature selection-classification model using the above mentioned methods are presented. …”
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    Article
  2. 2

    Use of hybrid classification algorithm for land use and land cover analysis in data scarce environment by Al-Doski, Jwan M. Mohammed

    Published 2013
    “…In conclusion, hybrid classification as a combination of k-means and support vector machine algorithms and post-classification comparison change detection technique can be used to monitor land cover changes in Halabja city, Iraq. …”
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    Thesis
  3. 3

    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

    Published 2022
    “…This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
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    Thesis
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  5. 5

    Identifying Cyberspace Users� Tendency in Blog Writing Using Machine Learning Algorithms by AbuSalim, S.W.G., Mostafa, S.A., Mustapha, A., Ibrahim, R., Wahab, M.H.A.

    Published 2023
    “…There is a specific proportion between blog features and bloggersâ�� tendency to social, political, and cultural patterns of different countries and nations that create trends among the bloggers in these countries. In this paper, we use an existing data set from previous research, which has 100 records of data, and manipulate the data by applying three machine learning algorithms for implementing classification and regression tasks. …”
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    Article
  6. 6

    The classification of wink-based eeg signals by means of transfer learning models by Jothi Letchumy, Mahendra Kumar

    Published 2021
    “…The implementation of pre-processing algorithms has been demonstrated to be able to mitigate the signal noises that arises from the winking signals without the need for the use signal filtering algorithms. …”
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    Thesis
  7. 7

    A Novel Approach to Estimate Diffuse Attenuation Coefficients for QuickBird Satellite Images: A Case Study at Kish Island, the Persian Gulf. by Pradhan, Biswajeet, Mohd Shafri, Helmi Zulhaidi, Mansor, Shattri, Kabiri, Keivan, Samim-Namin, Kaveh

    Published 2013
    “…Additionally, NASA-k d 490 algorithm was applied to determine k d 490 by using remotely sensed reflectance values of blue (R rs Blue ) and green (R rs Green ) bands in each pixel of QuickBird satellite image. …”
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    Article
  8. 8

    Detection and analysis of fake reviews on online service portal by Liong, Yong Xuan

    Published 2022
    “…In this paper, a framework of a Machine Learning based fake review detection model has been proposed to identify which classification algorithm is the most effective with the proposed framework.…”
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    Final Year Project / Dissertation / Thesis
  9. 9

    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. …”
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    Thesis
  10. 10

    Analytical framework for predicting online purchasing behavior in Malaysia using a machine learning approach by Mustakim, Nurul Ain

    Published 2025
    “…It is organized into three phases: preliminary investigation, implementation and analysis, and validation. The descriptive analysis examines purchasing behavior through correlation and regression analyses, while the predictive model uses decision trees (J48, Random Tree, REPTree), rule-based algorithms (JRip, OneR, PART), and clustering (K-Means) to identify patterns and predict trends. …”
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    Thesis
  11. 11

    An object-based approach to detect tree stumps in a selective logging area using Unmanned Aerial Vehicle imagery by Aisyah Marliza Muhmad Kamarulzaman, Wan Shafrina Wan Mohd Jaafar, Siti Nor Maizah Saad, Hamdan Omar, Mohd. Rizaludin Mahmud

    Published 2021
    “…Feature extraction and segmentation images to extract stumps from a UAV scene of a forested area in Ulu Jelai, Pahang provides a quick, automated method for identifying stumps. This research implemented a technique for detecting, segmenting, classifying, and measuring tree stumps by using the Multiresolution Segmentation Algorithm method. …”
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    Article
  12. 12

    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.…”
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    Thesis
  13. 13

    Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms by Teoh, Chin Chuang

    Published 2005
    “…The comparison showed that, the accuracy of the unsupervised classification map with value of 88.4% that was generated by using the cluster labelling algorithm was slightly more than the maximum-likelihood supervised classification map with value of 87.5%. …”
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    Thesis
  14. 14

    ABC: android botnet classification using feature selection and classification algorithms by Abdullah, Zubaile, Mohd Saudi, Madihah, Anuar, Nor Badrul

    Published 2017
    “…The Information Gain algorithm is used to select the most significant permissions, then the classification algorithms Naïve Bayes, Random Forest and J48 used to classify the Android apps as botnet or benign apps. …”
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    Article
  15. 15

    An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani by Ab Ghani, Nur Laila

    Published 2015
    “…The urban growth images obtained are analysed to improve existing classification algorithms. The improved algorithm is constructed by adding new parameter and classification rule to existing algorithm. …”
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    Thesis
  16. 16

    Classification of tropical rainforest using different classification algorithm based on remote sensing imagery: A study of Gunung Basor by Intan Noradybah Md Rodi

    Published 2019
    “…Thehighest accuracy for classification map of Gunung Basor is by using maximum likelihood algorithm with an accuracy of 82.90%. …”
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    Undergraduate Final Project Report
  17. 17

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

    Published 2004
    “…Case Slicing Technique (CST) helps in identifying the subset of features used in computing the similarity measures needed by classification algorithms. …”
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    Thesis
  18. 18

    An improve unsupervised discretization using optimization algorithms for classification problems by Mohamed, Rozlini, Samsudin, Noor Azah

    Published 2024
    “…Recognizing the critical role of discretization in enhancing classification performance, the study integrates equal width binning (EWB) with two optimization algorithms: the bat algorithm (BA), referred to as EB, and the whale optimization algorithm (WOA), denoted as EW. …”
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  19. 19

    An improve unsupervised discretization using optimization algorithms for classification problems by Mohamed, Rozlini, Samsudin, Noor Azah

    Published 2024
    “…Recognizing the critical role of discretization in enhancing classification performance, the study integrates equal width binning (EWB) with two optimization algorithms: the bat algorithm (BA), referred to as EB, and the whale optimization algorithm (WOA), denoted as EW. …”
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    Article
  20. 20

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

    Published 2022
    “…Classification is a data mining technique used to classify varied data types according to a specific criterion. …”
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    Thesis