Beyond temperature scaling:Obtaining well-calibrated multiclass probabilities with Dirichlet calibration

Class probabilities predicted by most multiclass classifiers are uncalibrated, often tending towards over-confidence. With neural networks, calibration can be improved by temperature scaling, a method to learn a single corrective multiplicative factor for inputs to the last softmax layer. On non-neural models the existing methods apply binary calibration in a pairwise or one-vs-rest fashion. We propose a natively multiclass calibration method applicable to classifiers from any model class, derived from Dirichlet distributions and generalising the beta calibration method from binary classification. It is easily implemented with neural nets since it is equivalent to log-transforming the uncalibrated probabilities, followed by one linear layer and softmax. Experiments demonstrate improved probabilistic predictions according to multiple measures (confidence-ECE, classwise-ECE, log-loss, Brier score) across a wide range of datasets and classifiers. Parameters of the learned Dirichlet calibration map provide insights to the biases in the uncalibrated model.Comment: Accepted for presentation at NeurIPS 201

Classifier Calibration: A survey on how to assess and improve predicted class probabilities

This paper provides both an introduction to and a detailed overview of the principles and practice of classifier calibration. A well-calibrated classifier correctly quantifies the level of uncertainty or confidence associated with its instance-wise predictions. This is essential for critical applications, optimal decision making, cost-sensitive classification, and for some types of context change. Calibration research has a rich history which predates the birth of machine learning as an academic field by decades. However, a recent increase in the interest on calibration has led to new methods and the extension from binary to the multiclass setting. The space of options and issues to consider is large, and navigating it requires the right set of concepts and tools. We provide both introductory material and up-to-date technical details of the main concepts and methods, including proper scoring rules and other evaluation metrics, visualisation approaches, a comprehensive account of post-hoc calibration methods for binary and multiclass classification, and several advanced topics

Diferenciais de rendimentos entre atividades agrícolas e não agrícolas no meio rural do Brasil

The objective of this study is to estimate income differentials between agricultural and nonagricultural activities in rural areas of the country. The data used are The objective of this study is to estimate income differentials between agricultural and nonagricultural activities in rural areas of the country. The data used are from PNAD (2015) and the models used were Blinder-Oaxaca and RIF Regression. It can be seen that nonagricultural activities generate higher incomes when compared to agricultural ones. Schooling is the variable that best explains the fact that nonagricultural activities earn higher incomes than agricultural ones.O objetivo desse estudo é estimar os diferenciais de rendimentos entre as atividades agrícolas e não agrícolas no meio rural do país. Os dados utilizados são provenientes da PNAD (2015) e os modelos usados foram Blinder-Oaxaca e RIF Regression. Constata-se que as atividades não agrícolas geram rendimentos maiores quando comparadas com as agrícolas. De todas as variáveis utilizadas na amostra, a escolaridade é a que explica melhor o fato de as atividades não agrícolas auferirem rendimentos superiores as agrícolas

Variabilidade Genética de Bovinos das Raças Guzerá e Senepol por Marcadores Microssatélites

Bovine production plays economic importance in Brazil and Guzerat and Senepol breeds are producer of meat. It was aimed to analyze the genetic variability of Guzerat and Senepol breeds by microsatellite markers. The breeds were collected and genotyped for ten microsatellite loci by automatic sequencer and statistically analysed. A total of 53 alleles were observed being the average number was 5.3 in both breeds. The effective numbers of alleles were 3.36 for Guzerat and 3.11 for Senepol cattle. The Shannon indexes were 1.36 for Guzerat and 1.26 for Senepol cattle. The expected heterozigosity were 0.71 and PIC values were 0.64 in both breeds. The FIS were 0.01 and 0.11 for Guzerat and Senepol breeds, respectively and Hardy-Weinberg equilibrium were P>0.05 for Guzerat and P<0.05 for Senepol cattle. The combined discrimination powers were 0.99 in both breeds and combined exclusion powers (PE1) were 0.99 in both breeds and combined exclusion powers (PE2) were 0.96 and 0.95 for Guzerat and Senepol breeds espectively. There is genetic variability in both breed, but there are evidences of inbreeding enabling genetic drift and should be necessary to use major number of microsatellite loci to analyze with high efficiency the exclusion power (PE2).A bovinocultura desempenha função importante na economia Brasileira e as raças Guzerá e Senepol são produtoras de carne. Objetivou-se analisar as variabilidades genéticas das raças Guzerá e Senepol através dos marcadores microssatélites. Os animais foram coletados e genotipados para dez locimicrossatélites em um sequenciador automático de DNA e analisado estatisticamente. Um total de 53 alelos foi observado com número médio de 3,36 para Guzerá e 3,11 para a raça Senepol. Os índices de Shannon foram 1,36 para Guzerá e 1,26 para raça Senepol. As heteroziosidades esperadas foram 0,71 e os valores de PIC foram 0,64 em ambas as raças. Os valores de FISforam 0,01 e 0,11 para Guzerá e Senepol, espectivamente e as proporções de Hardy-Weinberg foram não ignificativas em Guzerá (P>0,05) e significativas em Senepol (P<0,05). Os poderes de discriminação combinados foram 0,99 em ambas as raças e os poderes de exclusões combinados (PE1) foram 0,99 em ambas as raças e os poderes de exclusão combinados (PE2) foram 0,96 e 0,95 em Guzerá e Senepol, respectivamente. Existe variabilidade genética em ambas as raças, mas existem evidências de endocruzamentos por consequência da deriva genética e seria necessário avaliar um maior número de locimicrossatélites para aumentar a eficiência no poder de exclusão (PE2

La Televisión Digital Interactiva para el mejoramiento de los pueblos latinoamericanos

La línea de investigación y desarrollo presentada consiste en estudiar, desarrollar y evaluar aplicaciones de Televisión Digital Interactiva (TVDi) y tecnologías complementarias para el mejoramiento de los pueblos latinoamericanos. Uno de los principales objetivos es la formación de recursos humanos y fortalecimiento de la investigación mediante el trabajo intergrupal entre diferentes instituciones nacionales y extranjeras.Eje: Computación gráfica, imágenes y visualización.Red de Universidades con Carreras en Informátic