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Classification of tropical rainforest using different classification algorithm based on remote sensing imagery: A study of Gunung Basor
Published 2019“…Remote sensing technologies are used globally to derive some of crucial spatial variable parameter such as vegetation cover. Three different classification algorithm, minimum distance classifier, Mahalanobis distance classifier and maximum likelihood algorithm was applied to classify the forest area in Gunung Basor. …”
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Hyper-Heuristic Evolutionary Approach for Constructing Decision Tree Classifiers
Published 2021“…Classification and Regression Tree (CART) algorithm is one of the renowned decision tree induction algorithms to address the classification as well as regression problems. …”
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An approach for cross-site scripting detection and removal based on genetic algorithms.
Published 2014“…In this paper, we propose to explore an approach based on genetic algorithms that will be able to detect and remove cross-site scripting vulnerabilities from the source code before an application is deployed. …”
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4
Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd
Published 2022“…One of the most powerful machine learning methods to handle classification problems is the decision tree. There are various decision tree algorithms, but the most commonly used are Iterative Dichotomiser 3 (ID3), CART, and C4.5. …”
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5
Cross-site scripting detection based on an enhanced genetic algorithm
Published 2015“…In this paper, we propose to explore an approach based on genetic algorithms that will be able to detect cross-site scripting vulnerabilities in the source code before an application is deployed. …”
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Classification of Google Play application using decision tree algorithm on sentiment analysis of text reviews / Aqil Khairy Hamsani, Ummu Fatihah Mohd Bahrin and Wan Dorishah Wan A...
Published 2023“…To achieve these objectives, the methods employed involve data preprocessing and implementing the Decision Tree (DT) algorithm for classification. The classification model is trained and tested using various split ratios, and the optimal depth for the DT is determined through parameter tuning to achieve the best accuracy. …”
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Prevention And Detection Mechanism For Security In Passive Rfid System
Published 2013“…A GUI is created in a form of JAVA application to display data detected from tag. …”
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8
First Semester Computer Science Students’ Academic Performances Analysis by Using Data Mining Classification Algorithms
Published 2014“…The comparative analysis is also conducted to discover the best classification model for prediction. From the experiment, the models develop using Rule Based and Decision Tree algorithm shows the best result compared to the model develop from the Naïve Bayes algorithm. …”
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9
A multi-filter feature selection in detecting distributed denial-of-service attack
Published 2019“…Thus, making it hard to detect and successfully bypasses the detection mechanism. …”
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Decision tree method for fault causes classification based on RMS-DWT analysis in 275 kV transmission lines network
Published 2021“…The classifier performance of different parameters was also compared in a confusion matrix form to obtain the best classification results of the decision tree.…”
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The implications for ahybrid detection technique against malicious sqlattacks on web applications
Published 2025“…Accordingly, the aim of this study is to identify the latest SQL injection attacks based on user’s inputs in web application associated with remote server database, and to develop a new method based on dynamic detection technique to prevent SQL injection attacks. …”
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An approach to improve detecting and removing cross- site scripting vulnerabilities in web applications
Published 2015“…Many web applications are vulnerable to XSS and are attacked frequently. Most of the previously proposed approaches focused on preventing and detecting XSS attacks during runtime, after vulnerable applications are already deployed. …”
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13
Tree-based contrast subspace mining method
Published 2020“…Hence, this thesis presents the optimization of parameters values for the tree-based method by genetic algorithm. …”
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Decision tree method for fault causes classification based on rms-dwt analysis in 275 kv transmission lines network
Published 2023“…The classifier performance of different parameters was also compared in a confusion matrix form to obtain the best classification results of the decision tree. � 2021 by the authors. …”
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Classification of basal stem rot disease in oil palm using dielectric spectroscopy
Published 2018“…Without implementing any data reduction algorithm, the highest classification accuracy was found in SVM classifier with 79.55%. …”
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16
Comparison of machine learning algorithms for estimating mangrove age using sentinel 2A at Pulau Tuba, Kedah, Malaysia / Fareena Faris Francis Singaram
Published 2021“…The supervised machine learning algorithm, SVM and Decision Tree are used for the estimation of the mangrove age into young and mature. …”
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Characterisation of pineapple cultivars under different storage conditions using infrared thermal imaging coupled with machine learning algorithms
Published 2022“…Several types of machine learning algorithms were compared, including linear discriminant analysis, quadratic discriminant analysis, support vector machine, k-nearest neighbour, decision tree, and naïve Bayes, to obtain the best performance for the classification of pineapple cultivars. …”
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Processing and classification of landsat and sentinel images for oil palm plantation detection
Published 2022“…The parameters for ANN were later adjusted to identify the best ANN classification, resulting in an overall accuracy of 98.2857% and 0.9792 of kappa coefficient, and manages to effectively detect oil palm trees from the background.…”
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Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification
Published 2020“…Furthermore, using SVM requires the user to set certain parameters values, including kernel type and kernel parameters, since these parameters own a significant effect on the effectiveness of SVM. …”
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