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Diagnosis and recommender system for diabetes patient using decision tree / Nurul Aida Mohd Zamary
Published 2024“…The phase of this project is divided into data preprocessing, implementation of the decision tree algorithm, and evaluation of the algorithm and prototype. …”
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2
Evaluation of data mining classification and clustering techniques for diabetes / Tuba Pala and Ali Yilmaz Camurcu
Published 2014“…The success evaluation of data mining classification algorithms have been realized through the data mining programs Weka and RapidMiner. …”
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3
Sauvola Segmentation and Support Vector Machine-Salp Swarm Algorithm Approach for Identifying Nutrient Deficiencies in Citrus Reticulata Leaves
Published 2024“…In the next phase, the datasets are optimized using the Salp Swarm Algorithm (SSA), which improves classification accuracy. …”
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4
Optimizing the light gradient-boosting machine algorithm for an efficient early detection of coronary heart disease
Published 2024“…The LightGBM algorithm was selected for its efficiency in classification tasks, and Bayesian Optimization with Tree-structured Parzen Estimator (TPE) was employed to fine-tune its hyperparameters. …”
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Machine-learning approach using thermal and synthetic aperture radar data for classification of oil palm trees with basal stem rot disease
Published 2021“…To identify non-infected and BSR-infected trees, the WEKA tool version 3.8.5 was used for classification. …”
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6
Multi-label risk diabetes complication prediction model using deep neural network with multi-channel weighted dropout
Published 2025“…The early diagnosis of diabetes complications using risk factors remains underexplored, particularly with the application of Multi-Label Classification (MLC). …”
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7
Imbalanced multi-class power transformer fault data classification through Edited Nearest Neighbour-Manhattan-Random Forest
Published 2025“…The Edited Nearest Neighbour technique, shown to be effective in other O&G subdomains, is evaluated using the Random Forest algorithm, which is widely used for its precision and ability to handle non-linear datasets. …”
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8
Automated mold defects classification in paintings: a comparison of machine learning and rule-based techniques.
Published 2025“…Subsequently, these regions are classified as mold defects using either morphological filtering or machine learning models such as Classification and Regression Trees (CART) and Linear Discriminant Analysis (LDA). …”
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Flood prediction model for Kuala Terengganu area using predictive analytics
Published 2025“…The model aimed to classify flood occurrence into two categories: flood and no flood. Evaluation using a confusion matrix demonstrated that the Random Forest algorithm achieved the highest performance with accuracy of 98.04%. …”
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10
Deep learning-based breast cancer detection and classification using histopathology images / Ghulam Murtaza
Published 2021“…To reduce the misclassification, a feature selection algorithm (using information gain and principal component analysis schemes) is developed to elicit the most discriminative feature subset. …”
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11
Spectral features selection and classification of oil palm leaves infected by Basal stem rot (BSR) disease using dielectric spectroscopy
Published 2018“…Following the selection of significant frequencies, the features were evaluated using two classifiers, support vector machine (SVM) and artificial neural networks (ANN) to determine the overall and individual class classification accuracies. …”
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Assessment of near-infrared and mid-infrared spectroscopy for early detection of basal stem rot disease in oil palm plantation
Published 2013“…Results confirmed the usefulness and efficiency of spectra-based classification approach for fast screening of BSR.…”
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13
Classification Algorithms and Feature Selection Techniques for a Hybrid Diabetes Detection System
Published 2021“…K-nearest neighbor is used for classification of the diabetes dataset. …”
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Early diabetes risk prediction using Ant Colony Optimization algorithm / Nur Aisyatul Husna Ahmad Yusri and Rizauddin Saian
Published 2023“…Therefore, this study has developed a classification model for predicting early diabetes risk using an Ant Colony Optimization (ACO) algorithm. …”
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15
Performance analysis of machine learning algorithms for classification of infection severity levels on rubber leaves
Published 2023“…The chlorophyll content of each leaf was measured using SPAD meter. Four classification algorithms investigated in this study were artificial neural network (ANN), support vector machine (SVM), knearest neighbour (kNN) and random forest (RF). …”
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16
An improved directed random walk framework for cancer classification using gene expression data
Published 2020“…It is found that these findings would improve the early diagnosis methods of cancer classification.…”
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Mid-infrared spectroscopy for early detection of basal stem rot disease in oil palm
Published 2014“…The selected principal component scores were used in classification using linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), k-nearest neighbor (kNN) and Naive-Bayes (NB) multivariate classification algorithms. …”
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Multi-Class Multi-Level Classification of Mental Health Disorders Based on Textual Data from Social Media
Published 2024“…Overall, the MCML classification algorithm is proven to be used as a benchmark for early detection of text-based mental health disorders.…”
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Breast cancer disease classification using fuzzy-ID3 algorithm with FUZZYDBD method: automatic fuzzy database definition
Published 2021“…This paper proposed the fuzzy-ID3 (FID3) algorithm, a fuzzy decision tree as the classification method in breast cancer detection. …”
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Design of intelligent Qira’at identification algorithm
Published 2017“…To evaluate the algorithm, 350 samples for 10 types of Qira’at recitation are in used, and for justifying the best pattern classification, few algorithms are tested in the early preliminary evaluation with K-Nearest Neighbour, GMM and PPCA. …”
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