Search Results - (( java implementation mining algorithm ) OR ( diabetes classification based 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 -
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Accuracy and performance analysis for classification algorithms based on biomedical datasets
Published 2021“…Lazy based k-nearest neighbors (IBK) algorithm, and Rules-based OneR algorithm. …”
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Conference or Workshop Item -
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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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Classification of Diabetes Mellitus (DM) using Machine Learning Algorithms
Published 2021“…In this research, it was found that performance of ensemble method using hybrid classifier of Random Forest – Bayes Net model was found as the best DM classification model with an accuracy of 83.91% using the Pima Indian Diabetes Dataset (PIDD) out beating all the other classification algorithms. …”
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Final Year Project -
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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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Optimization of neural network using cuckoo search for the classification of diabetes
Published 2015“…In this paper, we proposed diabetes classifier based on the cuckoo search algorithm (CS) and Neural Network (NN). …”
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Diabetes Diagnosis And Level Of Care Fuzzy Rule-Based Model Utilizing Supervised Machine Learning For Classification And Prediction
Published 2024“…Overall, the proposed fuzzy rule-based diabetes diagnosis and level of care fuzzy model works well with most of the machine learning algorithms tested. …”
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Classification of Diabetes Mellitus using Ensemble Algorithms
Published 2021“…The objective of this study is to perform DM classification using various machine learning algorithms. …”
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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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Diabetic Retinopathy Detection Model using Hybrid of U-Net and Vision Transformer Algorithms
Published 2024“…Now, we present a hybrid model which is a combination of U-Net algorithm used for image segmentation and Vision Transformer for classification. …”
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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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Classification of diabetic retinopathy clinical features using image enhancement technique and convolutional neural network / Abdul Hafiz Abu Samah
Published 2021“…In general, this thesis introduces an automated machine learning algorithm for detecting diabetic retinopathy (DR) in fundus images. …”
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An improved diabetes risk prediction framework : An Indonesian case study
Published 2018“…However,there is the issue of noisy dataset detected as incomplete data and the outlier class problem that affects sampling bias.Existing frameworks were deemed difficult in identifying the critical risk factors of diabetes;some of which were considerably inaccurate and consume substantial computation time.The purpose of this study is to develop a suitable framework for predicting diabetes risks.From a complete blood test,the framework can predict and classify the output of either having diabetes risk or no diabetes risk.A Diabetes Risk Prediction Framework (DRPF) was developed from the literature review and case studies were afterwards conducted in three private hospitals in Semarang.Analyses were conducted to find a suitable component of the framework—due to lack of comparison and analysis on the combination of feature selection and classification algorithm.DRPF comprises four main sections: pre-processing,outlier detection,risk weighting,and learning. …”
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15
A proposed approach for diabetes diagnosis using neuro-fuzzy technique
Published 2022“…This paper proposed an approach for diagnosing diabetes using the adaptive neuro-fuzzy inference system (ANFIS) based on Pima Indians diabetes dataset (PIDD). …”
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Diabetic retinopathy detection using fusion of textural and optimized convolutional neural network features / Uzair Ishtiaq
Published 2024“…The hybrid approach based on image preprocessing and fusion of features is the foundation of the proposed classification method. …”
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An improved data classification framework based on fractional particle swarm optimization
Published 2019“…It can be concluded from the simulation results that the proposed MOFPSO-ERNN classification algorithm demonstrated good classification performance in terms of classification accuracy (Breast Cancer = 99.01%, EEG = 99.99%, PIMA Indian Diabetes = 99.37%, Iris = 99.6%, Thyroid = 99.88%) as compared to the existing hybrid classification techniques. …”
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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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