Supervised Machine Learning
Mostrando 1-12 de 33 artigos, teses e dissertações.
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1. CLOROFILA EXTRAÍDA DE RESÍDUO INDUSTRIAL DA ERVA-MATE (Ilex paraguaiensis) UMA POSSIBILIDADE DE ECONOMIA CIRCULAR
Chlorophyll is the most abundant green pigment on the planet, it is unstable and decomposes naturally. Mate-herb is a traditional native plant in the southern region of South America, and its tea is part of the local culture and extractive agriculture. The mate-herb industry generates as a by-product a resinous material rich in chlorophyll whose use is propo
Química Nova. Publicado em: 2022
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2. Prediction of impacts on liver enzymes from the exposure of low-dose medical radiations through artificial intelligence algorithms
SUMMARY OBJECTIVES: This study aimed to develop artificial intelligence and machine learning-based models to predict alterations in liver enzymes from the exposure of low annual average effective doses in radiology and nuclear medicine personnel of Institute of Nuclear Medicine and Oncology Hospital. METHODS: Ninety workers from the Radiology and Nuclear M
Rev. Assoc. Med. Bras.. Publicado em: 2021-02
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3. Preprocessing procedures and supervised classification applied to a database of systematic soil survey
ABSTRACT: Data Mining techniques play an important role in the prediction of soil spatial distribution in systematic soil surveying, though existing methodologies still lack standardization and a full understanding of their capabilities. The aim of this work was to evaluate the performance of preprocessing procedures and supervised classification approaches
Sci. agric. (Piracicaba, Braz.). Publicado em: 20/05/2019
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4. Development of a skateboarding trick classifier using accelerometry and machine learning
Abstract Introduction Skateboarding is one of the most popular cultures in Brazil, with more than 8.5 million skateboarders. Nowadays, the discipline of street skating has gained recognition among other more classical sports and awaits its debut at the Tokyo 2020 Summer Olympic Games. This study aimed to explore the state-of-the-art for inertial measurement
Res. Biomed. Eng.. Publicado em: 2017-10
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5. Algoritmos Evolutivos aplicados ao Classificador baseado em Segmentos de Reta / Evolutive Algorithms applied to the Straight Line Segment Classifier
During the past years, the use of machine learning techniques have become into one of the most frequently performed tasks, due to the large amount of pattern recognition applications such as: voice recognition, text classification, face recognition, medical image diagnosis, among others. Thus, a great number of techniques dealing with this kind of problem ha
IBICT - Instituto Brasileiro de Informação em Ciência e Tecnologia. Publicado em: 03/07/2012
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6. Melhoria da atratividade de faces em imagens = : Echancement of faces attractiveness in images / Echancement of faces attractiveness in images
O rosto desempenha um papel importante na comunicação e expressão de emoções. Por ser o cartão de visitas individual e caracterizar a primeira impressão de cada um, sua aparência e seu formato tornam-se alvo de diversos estudos. Um rosto mais atraente é capaz de capturar com maior facilidade não apenas a atenção de quem o observa, como também su
IBICT - Instituto Brasileiro de Informação em Ciência e Tecnologia. Publicado em: 29/06/2012
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7. Método baseado em rotação e projeção otimizadas para a construção de ensembles de modelos / Ensemble method based on optimized rotation and projection
The development of new techniques capable of inducing predictive models with low generalization errors has been a constant in machine learning and other related areas. In this context, the composition of an ensemble of models should be highlighted due to its theoretical and empirical potential to minimize the generalization error. Several methods for buildin
IBICT - Instituto Brasileiro de Informação em Ciência e Tecnologia. Publicado em: 31/05/2012
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8. Abordagens para aprendizado semissupervisionado multirrótulo e hierárquico / Multi-label and hierarchical semi-supervised learning approaches
In machine learning, the task of classification consists on creating computational models that are able to automatically identify the class of objects belonging to a predefined domain from a set of examples whose class is known a priori. There are some classification scenarios in which each object can be associated to more than one class at the same time. Mo
IBICT - Instituto Brasileiro de Informação em Ciência e Tecnologia. Publicado em: 25/10/2011
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9. Algoritmo de aprendizado supervisionado - baseado em máquinas de vetores de suporte - uma contribuição para o reconhecimento de dados desbalanceados / Supervised learning Algorithm - Based on Support Vector Machines - A Contribution to the Recognition of Unbalanced Data
The machine learning in datasets that have unbalanced classes, has received considerable attention in the scientific community, because the traditional classification algorithms dont provide a satisfactory performance. This low performance can be explained by the fact that the traditional techniques of machine learning consider that each class present in the
IBICT - Instituto Brasileiro de Informação em Ciência e Tecnologia. Publicado em: 26/09/2011
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10. Aprendizado semissupervisionado através de técnicas de acoplamento
O Aprendizado de Máquina (AM) pode ser visto como uma área de pesquisa dentro da Inteligência Artificial (IA) que busca o desenvolvimento de programas de computador que possam evoluir à medida que vão sendo expostos a novas experiências. O principal objetivo de AM é a busca por métodos e técnicas que permitem a concepção de sistemas computacionais
IBICT - Instituto Brasileiro de Informação em Ciência e Tecnologia. Publicado em: 17/02/2011
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11. Aprendizado semissupervisionado multidescrição em classificação de textos / Multi-view semi-supervised learning in text classification
Semi-supervised learning algorithms learn from a combination of both labeled and unlabeled data. Thus, they can be applied in domains where few labeled examples and a vast amount of unlabeled examples are available. Furthermore, semi-supervised learning algorithms may achieve a better performance than supervised learning algorithms trained on the same few la
Publicado em: 2010
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12. Semi-supervised learning based in disagreement by similarity / Classificação semi-supervisionada baseada em desacordo por similaridade
Semi-supervised learning is a machine learning paradigm in which the induced hypothesis is improved by taking advantage of unlabeled data. Semi-supervised learning is particularly useful when labeled data is scarce and difficult to obtain. In this context, the Cotraining algorithm was proposed. Cotraining is a widely used semisupervised approach that assumes
Publicado em: 2010