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  1. 1
    Phylogenetic tree classification system using machine learning algorithm

    Phylogenetic tree classification system using machine learning algorithm by Tan, Jia Kae

    Published 2015
    “…The aim is to detennine the suitable features for the phylogenetic tree image classification systeIlJ. …”
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    Final Year Project Report / IMRAD
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  2. 2
    Direct approach for mining association rules from structured XML data

    Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

    Published 2012
    “…The thesis also provides a two different implementation of the modified FLEX algorithm using a java based parsers and XQuery implementation. …”
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    Thesis
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  3. 3
    Case Slicing Technique for Feature Selection

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

    Published 2004
    “…CST was compared to other selected classification methods based on feature subset selection such as Induction of Decision Tree Algorithm (ID3), Base Learning Algorithm K-Nearest Nighbour Algorithm (k-NN) and NaYve Bay~sA lgorithm (NB). …”
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  4. 4
    VEHICLE CLASSIFICATION FROM CCTV IMAGES AND VIDEOS

    VEHICLE CLASSIFICATION FROM CCTV IMAGES AND VIDEOS by KAMARUDDIN, ERNA SHAFFIQA

    Published 2018
    “…The study is conducted to analyse the performance of histograms of oriented gradient(HOG) between Linear SVM algorithm and Aggregated Channel Features (ACF) algorithm which is using Decision Trees. …”
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  5. 5
    An extended ID3 decision tree algorithm for spatial data

    An extended ID3 decision tree algorithm for spatial data by Sitanggang, Imas Sukaesih, Yaakob, Razali, Mustapha, Norwati, Nuruddin, Ahmad Ainuddin

    Published 2011
    “…One of classification algorithms namely the ID3 algorithm which originally designed for a non-spatial dataset has been improved by other researchers in the previous work to construct a spatial decision tree from a spatial dataset containing polygon features only. …”
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  6. 6
    Classification model for hotspot occurrences using spatial decision tree algorithm

    Classification model for hotspot occurrences using spatial decision tree algorithm by Sitanggang, Imas Sukaesih, Yaakob, Razali, Mustapha, Norwati, Nuruddin, Ahmad Ainuddin

    Published 2013
    “…This study describes the application of data mining technique namely decision tree on forest fires data. We improved the ID3 decision tree algorithm such that it can be utilized on spatial data in order to develop a classification model for hotspots occurrence. …”
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  7. 7
    Enhanced dimensionality reduction methods for classifying malaria vector dataset using decision tree

    Enhanced dimensionality reduction methods for classifying malaria vector dataset using decision tree by Arowolo, Micheal Olaolu, Adebiyi, Marion Olubunmi, Adebiyi, Ayodele Ariyo

    Published 2021
    “…The proposed algorithm is used to fetch relevant features based from the high-dimensional input feature space. …”
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  8. 8
    Improved random forest for feature selection in writer identification

    Improved random forest for feature selection in writer identification by Sukor, Nooraziera Akmal

    Published 2015
    “…An algorithm and framework of Improved Random Forest (IRF) tree was applied for feature selection process. …”
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  9. 9
    Behavioural features for mushroom classification

    Behavioural features for mushroom classification by Ismail, Shuhaida, Zainal, Amy Rosshaida, Mustapha, Aida

    Published 2018
    “…The Principal Component Analysis (PCA) algorithm is used for selecting the best features for the classification experiment using Decision Tree (DT) algorithm. …”
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  10. 10
    Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals

    Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals by Too, Jing Wei

    Published 2020
    “…In this regard, this thesis proposes five FS methods for efficient EMG signals classification. The first method is the Binary Tree Growth Algorithm (BTGA), which implements a hyperbolic tangent function to convert the Tree Growth Algorithm into the binary version. …”
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  11. 11
    Study and Implementation of Data Mining in Urban Gardening

    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    Published 2019
    “…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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  12. 12
    Intersection Features For Android Botnet Classification

    Intersection Features For Android Botnet Classification by Ismail, Najiahtul Syafiqah, Yusof, Robiah, Saad, Halizah, Abdollah, Mohd Faizal, Yusof, Robiah

    Published 2019
    “…This paper proposed an enhancement approach for Android botnet classification based on features selection and classification algorithms. …”
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  13. 13
    Formulation of invariants for discrete orthogonal moments and image classification / Pee Chih Yang

    Formulation of invariants for discrete orthogonal moments and image classification / Pee Chih Yang by Pee, Chih Yang

    Published 2013
    “…Due to the complexity of hypergeometric functions, existing invariant algorithms are slow. In addition, some of the features have poor classification performance and are highly sensitive to the noise. …”
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  14. 14
    Classification of basal stem rot disease in oil palm using dielectric spectroscopy

    Classification of basal stem rot disease in oil palm using dielectric spectroscopy by Al-Khaled, Al-Fadhl Yahya Khaled

    Published 2018
    “…First, features selection algorithms (genetic algorithm (GA), random forest (RF), and support vector machine-feature selection (SVM-FS)) were used to select the most significant frequencies. …”
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  15. 15
    Earthquake multi-classification detection based velocity and displacement data filtering using machine learning algorithms

    Earthquake multi-classification detection based velocity and displacement data filtering using machine learning algorithms by Murti M.A., Junior R., Ahmed A.N., Elshafie A.

    Published 2023
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  16. 16
    Combining data mining algorithm and object-based image analysis for detailed urban mapping of hyperspectral images

    Combining data mining algorithm and object-based image analysis for detailed urban mapping of hyperspectral images by Hamedianfar, Alireza, Mohd Shafri, Helmi Zulhaidi, Mansor, Shattri, Ahmad, Noordin

    Published 2014
    “…The images were used to explore the combined performance of a data mining (DM) algorithm and object-based image analysis (OBIA). A large number of attributes were discovered with the C4.5 DM algorithm, which also generated the classification model as a decision tree. …”
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  17. 17
    Integrated approach using data mining-based decision tree and object-based image analysis for high-resolution urban mapping of WorldView-2 satellite sensor data

    Integrated approach using data mining-based decision tree and object-based image analysis for high-resolution urban mapping of WorldView-2 satellite sensor data by Hamedianfar, Alireza, Mohd Shafri, Helmi Zulhaidi

    Published 2016
    “…Many features were explored by using a DM algorithm, which created the classification rules as a decision tree (DT) structure from the first study area. …”
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  18. 18
    Scalable approach for mining association rules from structured XML data

    Scalable approach for mining association rules from structured XML data by Abazeed, Ashraf Riad, Mamat, Ali, Sulaiman, Md. Nasir, Ibrahim, Hamidah

    Published 2009
    “…Many techniques have been proposed to tackle the problem of mining XML data we study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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  19. 19
    Study Of EMG Feature Selection For Hand Motions Classification

    Study Of EMG Feature Selection For Hand Motions Classification by Abdullah, Abdul Rahim, Mohd Saad, Norhashimah, Too, Jing Wei

    Published 2019
    “…Thus, this paper employs two recent feature selection methods namely competitive binary gray wolf optimizer (CBGWO) and modified binary tree growth algorithm (MBTGA) to evaluate the most informative EMG feature subset for efficient classification. …”
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  20. 20
    Analysis of Acoustic Emission Signal for Prediction of Corrosion on Carbon Steel Pipelines

    Analysis of Acoustic Emission Signal for Prediction of Corrosion on Carbon Steel Pipelines by Kafi, N.A., May, Z.B.

    Published 2021
    “…Six features were selected to be used as input into the two algorithms. …”
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