Search Results - (( development class learning algorithm ) OR ( java data optimization algorithm ))
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1
An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…In the second phase, a classifier ensemble learning model is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on Binary Quantum Gravitational Search Algorithm (QBGSA), (ii) To mine data streams using various data chunks and overcome a failure of single classifiers based on SVM, MLP and K-NN algorithms. …”
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Thesis -
2
Fuzzy modeling using Bat Algorithm optimization for classification
Published 2018“…A Sazonov Engine which is a fuzzy java engine is use to apply Bat Algorithm in the experiment. …”
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Undergraduates Project Papers -
3
Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…Therefore, in this paper, we proposed Dynamic tasks scheduling algorithm based on attribute reduction with an enhanced hybrid Genetic Algorithm and Particle Swarm Optimization for optimal device selection. …”
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Article -
4
The impact of virtual reality on programming algorithm courses on student learning outcomes
Published 2024“…In the control class, students apply traditional learning, while the experimental class uses VR-based learning. …”
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Article -
5
Classification of diabetic patients with imbalanced class distribution by using a Cost-Sensitive forest algorithm / Ummi Asyiqin Che Muhammad and Muhammad Hasbullah Mohd Razali
Published 2023“…Although many machine learning algorithms have been developed by researchers, the class imbalanced distribution still makes it challenging for classifiers to properly learn and differentiate between the minority and majority classes. …”
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Book Section -
6
Kernel and multi-class classifiers for multi-floor wlan localisation
Published 2016“…The multi-class classification strategy is used to ensure quick estimation of the multi-class NN algorithms. …”
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Thesis -
7
E4ML: Educational Tool for Machine Learning
Published 2003“…There are various types of machine learning algorithms with certain processes taken by the algorithm.In teaching of the machine learning algorithms, such processes need to be explained especially to the beginner in introductory level.This paper discusses the development the tool that addresses the process by certain algorithm to produce a hypothesis or output based on given data.This tool can also be used in teaching and learning purposes.The explanation of processes by the algorithms is demonstrated through simple simulation.The source of the algorithms was adapted from Mitchell book [1] that cover popular algorithms in machine learning for teaching and learning such as Concept Learning, Decision Tree, Bayesian Learning, Neural Networks, and Instance based Learning.The tool also used several classes of Weka (Waikato Environment for Knowledge Analysis) as a basis for the design and implementation of the new tool that focuses on explaining the processes taken by certain algorithm.…”
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Conference or Workshop Item -
8
Mobile machine vision for railway surveillance system using deep learning algorithm
Published 2021“…In this paper, object detection model is developed and implemented with deep learning algorithm. …”
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Proceedings -
9
A random search based effective algorithm for pairwise test data generation
Published 2011“…This paper proposes an effective random search based pairwise test data generation algorithm named R2Way to optimize the number of test cases. …”
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Conference or Workshop Item -
10
A class skew-insensitive ACO-based decision tree algorithm for imbalanced data sets
Published 2021“…This condition impeded the entropy-based heuristic of existing ATM algorithm to develop effective decision boundaries due to its biasness towards the dominant class. …”
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Article -
11
Support directional shifting vector: A direction based machine learning classifier
Published 2021“…These vectors form a linear function to measure cosine-angle with both the target class data and the non-target class data. Considering target data points, the linear function takes such a position that minimizes its angle with target class data and maximizes its angle with non-target class data. …”
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Article -
12
Scalable approach for mining association rules from structured XML data
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Conference or Workshop Item -
13
EasyA: Easy and effective way to generate pairwise test data
Published 2013“…This paper proposes a matrix based calculation for pairwise test data generation algorithm named EasyA to optimize the number of test cases. …”
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Conference or Workshop Item -
14
A Reinforced Active Learning Algorithm for Semantic Segmentation in Complex Imaging
Published 2021“…We propose a new reinforced active learning strategy based on a deep reinforcement learning algorithm. …”
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Article -
15
Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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Thesis -
16
Machine learning algorithms in context of intrusion detection
Published 2016“…These machine learning algorithms develop a detection model in a training phase. …”
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Conference or Workshop Item -
17
An enhanced synthetic oversampling framework with self-supervised contrastive learning for multi-class image imbalance
Published 2025“…Class imbalance significantly affects the performance of machine learning and deep learning classifiers, especially in image recognition tasks where certain classes are underrepresented. …”
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Thesis -
18
DEEP LEARNING ALGORITHM IMPLEMENTATION FOR SHIP DETECTION IN SPOT SATELLITE IMAGES
Published 2019“…The deep-learning algorithm to be deployed is Faster R-CNN and to be implemented using MATLAB. …”
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Final Year Project -
19
Credit Card Fraud Detection Using New Preprocessing And Hybrid Machine Learning Techniques
Published 2023“…The higher ratio of majority to minority classes can lead to misleading results, as conventional machine learning algorithms assume equal class distribution. …”
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Thesis -
20
