Search Results - (( level classification approach algorithm ) OR ( java implementation tree algorithm ))
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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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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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IMPLEMENTATION OF IMAGE TEXTURE ANALYSIS USING GRAY LEVEL RUN LENGTH APPROACH
Published 2006“…With the dramatic increase of imaging techniques, there is a great demand for new approaches in texture analysis. This paper presents a new approach for texture analysis using statistical method and gray level run length matrix (GLRLM) approach as the second order statistics approach. …”
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…The method was implemented using Java and the results of the simulation were evaluated using five standard performance metrics: accuracy, AUC, precision, recall, and f-Measure. …”
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Imbalanced Classification Methods for Student Grade Prediction : A Systematic Literature Review
Published 2023“…The study also presents the most common balancing methods published from 2015 to 2021 and highlights their impact on resolving imbalanced classification in three approaches: data-level, algorithm-level, and hybrid-level. …”
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Jogging activity recognition using k-NN algorithm
Published 2022“…The k-NN algorithm is a simple and easy-to-implement supervised machine learning algorithm that can be used to solve both classification and regression problems. …”
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Academic Exercise -
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Imbalanced Classification Methods for Student Grade Prediction: A Systematic Literature Review
Published 2024“…The study also presents the most common balancing methods published from 2015 to 2021 and highlights their impact on resolving imbalanced classification in three approaches: data-level, algorithm-level, and hybrid-level. …”
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Gene subset selection for lung cancer classification using a multi-objective strategy
Published 2008“…It obtains encouraging result on the data set as compared with an approach that uses single-objective strategy in genetic algorithms.…”
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Deep learning framework for hierarchical-based object identification and description
Published 2024“…The Deep learning (DL) and Computer Vision (CV) approaches allow computers to gain high-level understanding from images or videos. …”
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Extremal region detection and selection with fuzzy encoding for food recognition
Published 2019“…In the third algorithm, a soft assignment technique using fuzzy encoding is used to transform low-level features into a higher-level feature representation. …”
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Classification algorithm for customer complaint using fuzzy approach
Published 2016“…The main challenge to extract the valuable information is a proper approach managing the complaint data, classification process and high level of uncertainties on the complaint and involvement of expertsâ�� opinion. …”
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Classification algorithm for customer complaint using fuzzy approach
Published 2016“…The main challenge to extract the valuable information is a proper approach managing the complaint data, classification process and high level of uncertainties on the complaint and involvement of expertsâ�� opinion. …”
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Classification model for chlorophyll content using CNN and aerial images
Published 2024“…The classification approach requires a discrete group for dependent variables instead of continuous numbers. …”
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Classification Of Cervical Cancer Stage From Pap Smear Tests
Published 2019“…The performance of the proposed classification algorithm gave satisfactory results of accuracy, 91.9% for KNN classification and 95.0% for SVM classification.…”
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Final Year Project -
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MEDCnet : A Memory Efficient Approach for Processing High-Resolution Fundus Images for Diabetic Retinopathy Classification Using CNN
Published 2025“…These detailed features are then utilized for classification based on standard machine learning algorithms. …”
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