Search Results - (( model evaluation tree algorithm ) OR ( miner classification based algorithm ))
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1
An adaptive ant colony optimization algorithm for rule-based classification
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. …”
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2
Adaptive parameter control strategy for ant-miner classification algorithm
Published 2020“…This paper presents a new hybrid Ant-Miner classification algorithm and ant colony system (ACS), called ACS-Ant Miner. …”
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3
Rule pruning techniques in the ant-miner classification algorithm and its variants: A review
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. …”
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4
Diagnosis and recommender system for diabetes patient using decision tree / Nurul Aida Mohd Zamary
Published 2024“…The project successfully achieved its objectives by analyzing the literature, developing the decision tree algorithm, and evaluating the accuracy of the model. …”
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5
Hybrid ant colony optimization and genetic algorithm for rule induction
Published 2020“…In this study, a hybrid rule-based classifier namely, ant colony optimization/genetic algorithm ACO/GA is introduced to improve the classification accuracy of Ant-Miner classifier by using GA. …”
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Early diabetes risk prediction using Ant Colony Optimization algorithm / Nur Aisyatul Husna Ahmad Yusri and Rizauddin Saian
Published 2023“…The ACO-based classification algorithm, Ant-Miner is used to train the diabetes dataset of 520 new diabetes or potential diabetes patients from Sylhet Diabetes Hospital in Sylhet, Bangladesh. …”
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7
A new ant based rule extraction algorithm for web classification
Published 2011“…Ant-Miner algorithm is also still lacking in efficiency, accuracy and rule simplicity because of the local minima problem.Therefore, the Ant-Miner algorithm needs to be improved by taking into consideration of the accuracy and rule simplicity criteria so that it could be used to classify Web documents data sets or any large data sets.The best attribute selection method for Web texts categorization is the combination of correlation-based evaluation with random search as the search method.However, this attribute selection method will not give the best performance in attributes reduction. …”
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Monograph -
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Laptop price prediction using decision tree algorithm / Nurnazifah Abd Mokti
Published 2024“…This research project focuses on developing a laptop price prediction model using the decision tree algorithm based on laptop specifications. …”
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9
Classification of Cervical Cancer Using Ant-Miner for Medical Expertise Knowledge Management
Published 2018“…In this paper, an ant colony optimization based classification algorithm, Ant-Miner is applied to analyze the cervical cancer data set. …”
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10
Visualisasi pohon sintaksis berasaskan model dan algoritma sintaks ayat bahasa Melayu
Published 2018“…These results proved that the algorithm and model, for syntactic tree output enhancement, are generalisable enough to be tested on other languages. …”
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11
Modeling forest fires risk using spatial decision tree
Published 2011“…This paper presents our initial work in developing a spatial decision tree using the spatial ID3 algorithm and Spatial Join Index applied in the SCART (Spatial Classification and Regression Trees) algorithm. …”
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12
A coalition model for efficient indexing in wireless sensor network with random mobility / Hazem Jihad Ali Badarneh
Published 2021“…The proposed model consists of Dynamic-Coalition framework, Static-Coalition algorithm, and Coalition-Based Index-Tree framework. …”
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13
Detecting Remote-To-Local (R2L) attack using Decision Tree algorithm / Ahmad Nasreen Aqmal Mohd Nordin
Published 2024“…The key results encompass dataset preprocessing, Decision Tree classification model training, user interface development, and the evaluation of the Decision Tree model's performance. …”
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14
Crytojacking Classification based on Machine Learning Algorithm
Published 2024journal::journal article -
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Comparison of malware detection model using supervised machine learning algorithms / Syamir Mohd Shahirudin
Published 2022“…The objective of this project is to develop the Windows malware detection model using supervised machine learning in Decision Tree, K-NN and Naïve Bayes, to evaluate the performance of malware detection in term of testing and training of the features selection and to compare the accuracy detection model in all three machine learning algorithms. …”
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Student Project -
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Ant colony optimization for rule induction with simulated annealing for terms selection
Published 2012“…Seventeen data sets which consist of discrete and continuous data from a UCI repository are used to evaluate the performance of the proposed algorithm.Promising results are obtained when compared to the Ant-Miner algorithm and PART algorithm in terms of average predictive accuracy of the discovered classification rules.…”
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A class skew-insensitive ACO-based decision tree algorithm for imbalanced data sets
Published 2021“…This study proposed an enhanced algorithm called hellingerant-tree-miner (HATM) which is inspired by ant colony optimization (ACO) metaheuristic for imbalanced learning using decision tree classification algorithm. …”
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Semi-automatic oil palm tree counting from pleiades satellite imagery and airborne LiDAR / Nurul Syafiqah Khalid
Published 2020“…The study is to categorize and evaluates methods for automatic tree counting detection. …”
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19
Prediction of Oil Palm Yield Using Machine Learning in the Perspective of Fluctuating Weather and Soil Moisture Conditions: Evaluation of a Generic Workflow
Published 2023“…The prediction was followed by data preprocessing and feature selection. Selected regression models were compared with Random Forest, Gradient Boosting, Decision Tree, and other non-tree algorithms to prove the R2 driven performance superiority of tree-based ensemble models. …”
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