Search Results - (( basic reporting learning algorithm ) OR ( java implementation mining algorithm ))
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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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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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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 -
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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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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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Intelligent agent for e-commerce using genetic algorithm / Kok Sun Sun
Published 2000“…This system is achieved using the Genetic Algorithm which is capable of performing information retrieval and learning algorithm. …”
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9
A hybrid particle swarm optimization - extreme learning machine approach for intrusion detection system
Published 2018“…This work proposes the extreme learning machine (ELM) is one of the poplar machine learning algorithms which, easy to implement with excellent learning performance characteristics. …”
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10
Segmentation and Grading of Sinus Images
Published 2010“…This report discusses the research done and basic understanding of the proposed topic, which is Segementation and Grading of Sinus Images. …”
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Final Year Project -
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Designing an integrated AIOT system for tracking class attendance
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Raspberry Pi-Based Finger Vein Recognition System Using PCANet
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CFD modeling on coal properties towards the burnout efficiency
Published 2024text::Final Year Project -
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Predictive modeling and feature attribution of CO₂ adsorption on LDH-derived materials using machine learning approach
Published 2025“…Layered double hydroxides (LDH) are one of the efficient materials used for carbon capture applications. We report the application of six machine learning models, namely Random Forest (RF), gradient boosting decision tree (GBDT), extreme gradient boosting (XGBoost), Light gradient boosting machine (LightGBM), categorical boosting (CatBoost), and Adaptive boosting (AdaBoost) to predict CO2 adsorption capacity on LDH-derived materials. …”
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UV-vis spectrophotometric and artificial neural network for estimation of ammonia in aqueous environment using cobalt(II) ions
Published 2024“…A set of absorbance data for the [Co(NH3)(6)](2+) complex at selected wavelengths was input for ANN training using a back-propagation algorithm. The trained network with 22 hidden neurons, a 28 500 epoch number and 0.001% learning rate has extended the dynamic NH3 concentration range to 0.6-5.9 mM with a calibration error as low as 0.0649 x 10(-3). …”
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Integrated artificial intelligence-based classification approach for prediction of acute coronary syndrome
Published 2014“…In the development of the “hybrid AI-based” classification models, the proposed model (K1-K2- NN), was basically introduced through combining AI approaches of modified K-NN, genetic algorithm (GA), Fisher’s discriminant ratio (FDR) and class separability criteria (CSC). …”
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