machine learning
Adversarial machine learning: denial of services recognition
... Transfer learning is an area of machine learning which focuses on the transfer of knowledge be- tween models. This range of techniques is especially useful in computer vision, where training a new ...
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Electricity price forecasting utilizing machine learning in MIBEL
... Short term electricity price forecasts have become increasingly important in the last few decades due to the rise of more competitive electricity markets throughout the globe. Accurate forecasts are now essential for ...
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Machine learning and its applications to biology.
... some machine learning approaches over other categories of ...of machine learning approaches on a given problem is sometimes a matter of the quality indices used to evaluate the results, and ...
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MACHINE LEARNING TECHNIQUES USED IN BIG DATA
... Because of these issues, the researchers have made efforts in order to find alternative techniques for analysis of large amount of data. Thereby, the interest for machine learning has rapidly growth.As the ...
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Exploration of machine learning techniques for automatic optical inspection
... Assim sendo, o objetivo principal deste projeto é o de desenvolver uma solução que reconheça padrões nas imagens anómalas resultantes do processo de inspeção ótico das wafers e que sugira uma classificação dessa anomalia ...
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Feature selection for speech emotion recognition in Spanish and Basque: on the use of machine learning to improve human-computer interaction.
... Several Machine Learning paradigms were used for the emotion classification ...instance-based learning algorithm using feature subset selection techniques based on evolutionary algorithms is the best ...
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A Trading Agent Framework Using Plain Strategies & Machine Learning
... These results were created after several iterations of empirical refinement of the paramenters on the plain strategy and executions on simulation mode, as presented in 3.1. As we can observe, the results were clearly ...
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A Heuristic Approach to the Disease Diagnose System Using Machine Learning Algorithms (An Expert Advisory System for EMU Bird’s Diseases)
... of machine learning system is ...The machine learning architecture[6,13] consists of 3 systems ...of machine learning algorithms where the set of feasible points of upper level ...
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Forecasting Stock Markets Using Machine Learning
... model. Machine Learning algorithms have been widely used to predict financial markets with some degree of ...other Machine Learning algorithms through the application of significance ...
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Deteção de fraude em telecomunicações através de machine learning
... Specifically, this dissertation focused on an operator’s database, with information about calls received in a gateway, aiming to identify frauds such as bypass and wangiri. Firstly, an exploratory analysis based on ...
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Aplicação de Algoritmos de Aprendizado de Máquina no Apoio a Elaboração de Planos Nutricionais / Application of Machine Learning Algorithms to Support the Development of Nutritional Plans
... de Machine Learning (Regressão Linear, SVM – Support Vector Machine, Random Forest e Redes Neurais ...de Machine Learning apresentam desempenho melhor que os outros modelos na previsão ...
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Application of machine learning for real-time evaluation of salinity (or TDS) in drinking water using photonic sensors
... a machine learning algorithm of the naive Bayesian type, a sequence of statistical algorithms implemented in MATLAB with reference to training data to analyse the sample ...
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Risk assessment of atmospheric emissions using machine learning
... gorithms in the atmospheric sciences can be found in Gard- ner and Dorling (1998). Marzban (1995, 1997, 1998) and Hsieh (2003) have used artificial neural networks to improve model forecasts of tornadoes, wind ...
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Machine learning no processo de risco de crédito das instituições bancárias
... Neste item, apresentou-se as interpretações e ilações auferidas dos dados dos questionários feitos por este estudo. Assim sendo, organizou-se este item por subtítulos relacionados às questões dos questionários. O ...
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Prediction errors in learning drug response from gene expression data - influence of labeling, sample size, and machine learning algorithm.
... the Machine Learning Methods H2.1: The machine learning algorithms used for the prediction task at hand have a strong influence on the ...
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Machine Learning for incomplete data
... Methods based on basis functions (such as the sigmoid and q-Gaussian functions) and similarity measures (such as distances or kernel functions) are widely used in machine learning and related fields. These ...
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Machine learning: O Uso da Inteligência Artificial na Medicina/ Machine learning: The Use of Artificial Intelligence in Medicine
... o Machine learning (ML- aprendizado de máquina) fornece um caminho para melhorar a precisão e a confiabilidade das modalidades diagnósticas e tem o potencial de contribuir significativamente para alcançar o ...
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Classification Of Complex UCI Datasets Using Machine Learning And Evolutionary Algorithms
... Abstract: Classification is an important data mining technique with broad applications. Classification is a gradual practice for allocating a given piece of input into any of the known category. The Data Mining refers to ...
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Machine learning for biomedical literature triage.
... Machine learning from imbalanced data is a common problem of many real world applications beyond genomics text classification [9], such as fraud detection [10] [11], medical diagnosis [12] [13] and speech ...
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Visão auxiliar: aplicação de machine learning no auxílio a visão / Auxiliary vision: machine learning application in vision aid
... like machine learning, and through Application Programming Interfaces (API), this project proposes the development of a mobile application for people that has visual ...
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