hybrid machine learning
COVID-19 Pandemic Prediction for Hungary; a Hybrid Machine Learning Approach
... with machine learning can be classified in two ...state-of-the-art machine learning methods for outbreak modeling suggest two major research gaps for machine learning to ...
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An Effective Hybrid Machine Learning Approach for Coreference Resolution
... a hybrid machine learning ap- proach for coreference ...active learning method to gen- erate combined features so as to make ex- isted features used more effectively; at last, we proposed a ...
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A Hybrid Machine Learning based Approach for Hindi License Plate Recognition
... on hybrid machine learning techniques such as support vector machine and artificial neural ...different machine learning approachs are integrated in order to improve the ...
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Improve the Performance of a Complex FMS with a Hybrid Machine Learning Algorithm
... of machine learning technology, this problem is provided with more possibilities for the ...a hybrid machine learning algorithm, inte- grating genetic algorithm and reinforcement ...
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A Hybrid Machine Learning Method for Intrusion Detection
... According to the results presented in Table 3, SVM runs faster than the other two methods. We expected this because SVM classification is accomplished in a binary manner; which is, data is divided into two categories; ...
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An Experimental Study of Hybrid Machine Learning Models for Extracting Named Entities
... The results of our experimental evaluation of the proposed hybrid neural network Gated-CNN- CRF model proposed for NER task are described in the paper. For comparison, the experiments were also performed for ...
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Comparative Analysis of ANN-ICA and ANN-GWO for Crop Yield Prediction
... and machine learning ...two hybrid machine learning methods for the prediction of crop yield, for the first time in the ...that hybrid machine learning methods are ...
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Adaptive Distributed Intrusion Detection using Hybrid K means SVM Algorithm
... In this paper we proposed a hybrid approach for Intrusion Detection System. We presented adaptive and distributed model for Intrusion Detection System. The method uses the data collected by the sniffer agents of ...
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Heart Disease and Alzheimer Prediction based on Hybrid Classification Algorithm
... and hybrid algorithm demonstrate that hybrid machine learning techniques perform better than the individual algorithms on selected medical ...proposed hybrid algorithm composed of ...
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Performance Analysis of Combine Harvester using Hybrid Model of Artificial Neural Networks Particle Swarm Optimization
... the machine performance can dramatically minimize the wastes during harvesting, and it is also beneficial to machine ...computing, machine learning and optimization methods that had been used ...
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Plagiarism detection through internet using hybrid artificial neural network and support vectors machine
... solution. Machine learning methods like k- nearest neighbors (KNN), support vector machine (SVM), artificial neural networks (ANN) is a technique that is commonly used in solving the problem based on ...
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CLASSIFYING ARABIC TEXT USING DEEP LEARNING
... a hybrid machine learning algorithm which hybridizes the decisive functions of two topmost machine learning algorithms (Naïve Bays and Decision Tree) to holistically characterize and ...
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Agro Genius: Crop Prediction using Machine Learning
... Abstract:- This paper present a way to aid farmers focusing on profitable vegetable cultivation in Sri Lanka. As agriculture creates an economic future for developing countries, the demand of modern technologies in this ...
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Automatically identifying the function and intent of posts in underground forums
... of machine learning which predicts the most probably label y for an instance X (in our case a ...document). Machine learning may gen- erally be supervised to some degree by human labelled ...
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Machine Learning for Hybrid Machine Translation
... We describe a substitution-based system for hybrid machine translation (MT) that has been extended with machine learning components controlling its phrase selection. The approach is based on a ...
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Discovering Anomalous Rules In Firewall Logs Using Data Mining And Machine Learning Classifiers
... a hybrid model based on data mining and some of machine learning classifiers is proposed for analyzing and discovering anomalies in firewall ...
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Hybrid Intrusion Detection using Machine Learning for Wireless Sensor Networks
... supervised learning model, which analyses the data using learning algorithms, data can be used for regression or ...vector machine defines margin for attack and normal data based on predictor ...
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The Design of Hybrid Crop Recommendation System using Machine Learning Algorithms
... a hybrid model for recommending crops to south Indian states by considering various ...a hybrid model using the classifier algorithm such as Naive Bayes, J48 and association ...proposed hybrid ...
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Cost Optimized Hybrid System in Digital Advertising using Machine Learning
... through machine learning in predictive analytics and audience ...individual. Machine learning algorithms perform analysis on individual‟s personal data that they voluntarily share with ...
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Online Full Text
... We then compared several methods, including PseAACIndex-Profile, SVM-DT[27], SVM-pairwise, SVM-LA[19], SVM-PDT-Profile[23], BioSVM-2L[22], HHSearch[23], and disPseACC[28], with the SVM-hybrid method. We adopted ...
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