Search Results - (( java implementation mining algorithm ) OR ( using pre learning 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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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
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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8
A comparative analysis of machine learning algorithms for diabetes prediction
Published 2024“…Nine features which are Age, Blood pressure, Skin thickness, Glucose, Diabetes pedigree function, Pregnancy, BMI, Insulin level, and Outcome been used for the prediction of diabetes. The methodology involves data collection, pre-processing, and training the algorithms using k-fold cross-validation. …”
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9
Effects of Different Pre-Trained Deep Learning Algorithms as Feature Extractor in Tomato Plant Health Classification
Published 2023“…Five different pre-trained deep learning algorithms (i.e. Resnet-50, AlexNet, GoogleNet, VGG16, and VGG19) were studied and compared. …”
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10
Effects of Different Pre-Trained Deep Learning Algorithms as Feature Extractor in Tomato Plant Health Classification
Published 2023“…Five different pre-trained deep learning algorithms (i.e. Resnet-50, AlexNet, GoogleNet, VGG16, and VGG19) were studied and compared. …”
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11
Effects of Different Pre-Trained Deep Learning Algorithms as Feature Extractor in Tomato Plant Health Classification
Published 2023“…Five different pre-trained deep learning algorithms (i.e. Resnet-50, AlexNet, GoogleNet, VGG16, and VGG19) were studied and compared. …”
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12
Effects of Different Pre-Trained Deep Learning Algorithms as Feature Extractor in Tomato Plant Health Classification
Published 2023“…Five different pre-trained deep learning algorithms (i.e. Resnet-50, AlexNet, GoogleNet, VGG16, and VGG19) were studied and compared. …”
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13
Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof
Published 2019“…From the reviews, it is evident that autonomous system is set to handle finite number of encountered states using finite sequences of actions. In order to learn the optimized states-action policy the self-learning algorithm is developed using hybrid AI algorithm by combining unsupervised weightless neural network, which employs AUTOWiSARD and reinforcement learning algorithm, which employs Q-learning. …”
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14
Neural network algorithm development for Ion Sensitive Field Effect Transistor (ISFET) sensor / Muhammad Nasrul Hakim Adenan
Published 2013“…Backpropagation is used as the learning method of ANN model. The algorithm will be developed in MATLAB. …”
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15
Neural network algorithm development for Ion Sensitive Field Effect Transistor (ISFET) sensor: article / Muhammad Nasrul Hakim Adenan and Maizatul Zolkapli
Published 2013“…Backpropagation is used as the learning method of ANN model. The algorithm will be developed in MATLAB. …”
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16
Computational Thinking Through Unplugged Programming Activities : Exploring Students’ Learning Experiences
Published 2019“…However, the mean for post-test score is slightly higher than the mean for pre-test score. From the responses gathered through the interview sessions, four theme which are Good Learning Quality, Much Knowledge, Easy and Useful have been derived.…”
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17
Multi-Class Multi-Level Classification of Mental Health Disorders Based on Textual Data from Social Media
Published 2024“…The Multi-Class Multi-Level (MCML) classification algorithm was applied to perform detailed classification and address the limitations of the research scope using several approaches, including machine learning, deep learning, and transfer learning approaches. …”
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18
Autism Spectrum Disorder Classification Using Deep Learning
Published 2021“…Recently, deep learning methods have significantly sharpened the cutting edge of learning algorithms in a wide range of artificial intelligence tasks. …”
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19
One day ahead daily peak hour load forecasting by using invasive weed optimization learning algorithm based Artificial Neural Network
Published 2012“…By using 'seen' and 'unseen' of electrical energy demand data were used to test the performance of the proposed algorithm. …”
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Student Project -
20
Optimisation of fed-batch fermentation process using deep reinforcement learning
Published 2023“…The performance of the proposed algorithm was compared with a pre-determined exponential feeding profile and a genetic algorithm. …”
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Thesis
