Search Results - (( java implication based algorithm ) OR ( early classification technique algorithm ))
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Classification Algorithms and Feature Selection Techniques for a Hybrid Diabetes Detection System
Published 2021“…The proposed method has three steps: preprocessing, feature selection and classification. Several combinations of Harmony search algorithm, genetic algorithm, and particle swarm optimization algorithm are examined with K-means for feature selection. …”
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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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Performance analysis of machine learning algorithms for classification of infection severity levels on rubber leaves
Published 2023“…This work shows that the spectroscopic measurement combined with classification techniques are promising strategy to classify severity level of WRD based on the spectral data of the rubber leaves.…”
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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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5
Ganoderma boninense disease detection by near-infrared spectroscopy classification: a review
Published 2021“…Remarkably, (i) spectroscopy techniques are more reliable than other detection techniques such as serological, molecular, biomarker-based sensor and imaging techniques in reactions with organic tissues, (ii) the NIR spectrum is more precise and sensitive to particular diseases, including G. boninense, compared to visible light and (iii) hand-held NIRS for in situ measurement is used to explore the efficacy of an early detection system in real time using ML classifier algorithms and a predictive analytics model. …”
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A novel framework for potato leaf disease detection using an efficient deep learning model
Published 2022“…Thus, an accurate automated technique for timely detection and classification is needed to cope with the aforementioned challenges.There exist techniques grounded on machine learning and deep learning procedures that use the existing dataset i.e., â��The Plant Village Datasetâ�� and perform classification into only two classes in potato leaves. …”
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A novel framework for potato leaf disease detection using an efficient deep learning model
Published 2022“…Thus, an accurate automated technique for timely detection and classification is needed to cope with the aforementioned challenges.There exist techniques grounded on machine learning and deep learning procedures that use the existing dataset i.e., â��The Plant Village Datasetâ�� and perform classification into only two classes in potato leaves. …”
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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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Performances analysis of heart disease dataset using different data mining classifications
Published 2018“…There are many studies that explore the different classification algorithms for classification and prediction of heart disease. …”
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A fuzzy approach for early human action detection / Ekta Vats
Published 2016“…iii Finally, the proposed method is analyzed from a broader perspective and a hybrid technique for early anticipation of human action is proposed. …”
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Classification of Emphysema Patterns in Computed Tomography Based On Gabor Filter
Published 2015“…One of the main processing technique in CAD is texture classification and analysis. …”
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Final Year Project -
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First Semester Computer Science Students’ Academic Performances Analysis by Using Data Mining Classification Algorithms
Published 2014“…The comparative analysis is also conducted to discover the best classification model for prediction. From the experiment, the models develop using Rule Based and Decision Tree algorithm shows the best result compared to the model develop from the Naïve Bayes algorithm. …”
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Breast cancer disease classification using fuzzy-ID3 algorithm with FUZZYDBD method: automatic fuzzy database definition
Published 2021“…FID3 algorithm combined the fuzzy system and decision tree techniques with ID3 algorithm as the decision tree learning. …”
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Accuracy and performance analysis for classification algorithms based on biomedical datasets
Published 2021“…The study suggests finding a classifier among the most common kinds of classification algorithms within a combined approach represent in Bayesian, Trees, Rules, Function, and lazy algorithms to automate a better performance of early detection of diseases from the medical datasets. …”
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Early autism spectrum disorder detection using machine learning / Muhammad Shahmi Shahron Nizan
Published 2023“…The project follows a modified waterfall approach, focusing on creating a user-friendly interface and integrating the Random Forest Classification Algorithm for accurate detection. The results show the algorithm's impressive performance with an 86% precision in predicting ASD traits. …”
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Gene Selection For Cancer Classification Based On Xgboost Classifier
Published 2022“…The problem of having obstacle to making early detection for cancer is still a difficulty for the researcher. …”
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Undergraduates Project Papers -
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Classification of diabetic retinopathy clinical features using image enhancement technique and convolutional neural network / Abdul Hafiz Abu Samah
Published 2021“…To improve the performance from current systems, this work has investigation on different of image pre-processing enhancement technique to support accuracy on deep learning for DR classification. …”
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Evaluation of K-fold value in breast cancer diagnosis technique using SVM and bio-inspired optimization algorithm (JA-ABC5)
Published 2023“…Classification techniques can be used to improve the accuracy of breast cancer diagnosis to get around this limitation. …”
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