Search Results - (( java application based algorithm ) OR ( using vector ((tree algorithm) OR (new algorithm)) ))
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…Studies have shown how user perception can have a strong influence on policies and decision-making processes in a place, society, and nation. This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
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A comparison of support vector machine and decision tree classifications using satellite data of Langkawi Island
Published 2009“…This study investigates a new approach in image classification. Two classifiers were used to classify SPOT 5 satellite image; Decision Tree (DT) and Support Vector Machine (SVM). …”
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Parsing algorithms for grammars with regulated rewriting
Published 2011“…This unification allows approaching the membership (parsing) problem in formal language theory in the new point of view: instead of a usual derivation tree, one can use a Petri net derivation tree in which the control mechanism is also considered as a part of the tree. …”
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Proceeding Paper -
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Intrusion Detection Systems, Issues, Challenges, and Needs
Published 2021“…However, these algorithms suffer from many lacks especially when apply to detect new type of attacks, and need for new algorithms such as JAYA algorithm, teaching learning-based optimization algorithm (TLBO) algorithm is arise. …”
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Detection and classification of conflict flows in SDN using machine learning algorithms
Published 2021“…As a result, this paper presents several machine learning algorithms that include Decision Tree (DT), Support Vector Machine (SVM), Extremely Fast Decision Tree (EFDT) and Hybrid (DT-SVM) for detecting and classifying conflicting flows in SDNs. …”
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Detection of eye movements based on EEG signals and the SAX algorithm
Published 2018“…We would like to investigate another technique, namely the Symbolic Aggregate Approximation (SAX) algorithm, to find out its suitability and performance against known classification algorithms such as Support Vector Machine (SVM), k-Nearest Neighbour (KNN) and Decision Tree (DT).…”
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Named entity recognition using a new fuzzy support vector machine.
Published 2008“…Some of the Machine learning algorithms used in NER methods are, support vector machine(SVM), Hidden Markov Model, Maximum Entropy Model (MEM) and Decision Tree. …”
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A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem
Published 2016“…In addition, the classifier is also optimized such that it has a good generalization property. The main keys of the new classifier are based on the new kernel method, new learning metric and a new optimization algorithm in order to optimize the SVM decision function. …”
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Early prediction of acute kidney injury using machine learning algorithms
Published 2018“…The problem that has been considered in this study is the detection of acute kidney injury (AKI). The ML algorithms are Support Vector Machine (SVM), Neural Network (NN), Deep learning, Decision trees and Naiive Bayes. …”
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10
Power line corridor vegetation encroachment detection from satellite images using retinanet and support vector machine
Published 2023“…In this dissertation, a new vegetation encroachment detection method was proposed by studying the feasibility of using the visible-light band of highresolution satellite images using the RetinaNet deep learning model and Support Vector Machine algorithm (SVM). …”
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Prediction of stroke disease using machine learning techniques / Syarifah Adilah Mohamed Yusoff ... [et al.]
Published 2024“…This study has investigated five commonly used machine learning algorithm to be constructed as potential models for predicting stroke dataset. …”
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Improved tree routing protocol in zigbee networks
Published 2010“…ImpTR protocol uses an approach to select next hope depending on new algorithm and uses the same tree topology construction for distributing address to all sensor nodes in the network. …”
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Diagnosis and treatment recommender system for myocardial infarction using decision tree and Support Vector Machines (SVM) / Wan Marzuqiamrin Wan Mansor
Published 2025“…This project presents the development process of the prototype for diagnosis and treatment recommender system for myocardial infarction using decision tree and support vector machine (SVM) algorithms. …”
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Machine learning algorithms on price and rent predictions in real estate: A systematic literature review / Muhamad Harussani Abdul Salam ... [et al.]
Published 2022“…This study will provide new insights on the Machine Learning Algorithms in the real estate industry.…”
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Novel approach for IP-PBX denial of service intrusion detection using support vector machine algorithm
Published 2021“…In this research, Support Vector Machine (SVM) machine learning detection & prevention algorithm were developed to detect this type of attacks Two other techniques were benchmarked decision tree and Naïve Bayes. …”
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A new history matching sensitivity analysis framework with random forests and Plackett-Burman design
Published 2017“…Hence, parameters with low impact on the history matching error are discarded, and the remaining are used for Genetic Algorithm-based automatic history matching. …”
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Wearable based-sensor fall detection system using machine learning algorithm
Published 2021“…Then, a Machine Learning Algorithm (MLA) is used to train and test the data before a classifier is used to classify the new incoming dataset. …”
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Proceeding Paper -
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Image Classification for Age-related Macular Degeneration Screening Using Hierarchical Image Decompositions and Graph Mining
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Translating conventional wisdom on chicken comb color into automated monitoring of disease-infected chicken using chromaticity-based machine learning models
Published 2024“…Logistic Regression, Support Vector Machines (SVMs), K-Nearest Neighbors (KNN), and Decision Trees have been developed to detect infected chickens using the chromaticity data. …”
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