Search Results - (( developing class learning algorithm ) OR ( java implementation mining algorithm ))
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1
Direct approach for mining association rules from structured XML data
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 -
2
Study and Implementation of Data Mining in Urban Gardening
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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Article -
3
Scalable approach for mining association rules from structured XML data
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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4
Mining association rules from structured XML data
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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5
A web-based implementation of k-means algorithms
Published 2022“…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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Final Year Project / Dissertation / Thesis -
6
Image clustering comparison of two color segmentation techniques
Published 2010“…The clustering research is regarding the area of data mining and implementation of the clustering algorithms. …”
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7
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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8
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 -
9
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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10
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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11
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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12
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 -
13
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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14
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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15
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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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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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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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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20
Distributed Online Averaged One Dependence Estimator (DOAODE) Algorithm for Multi-class Classification of Network Anomaly Detection System
Published 2019“…Therefore, this paper aims to develop an effective and efficient network anomaly detection system by using distributed online averaged one dependence estimator (DOAODE) classification algorithm for multi-class network data to overcome these issues. …”
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