Results 81 to 90 of about 131,180 (321)
Machine Learning and Knowledge ExtractionIn machine learning, the Bayes classifier represents the theoretical optimum for minimizing classification errors. Since estimating high-dimensional probability densities is impractical, simplified approximations such as naïve Bayes and k-nearest ...
Quirin Stier +2 more
doaj +1 more source
Statistical Science and Philosophy of Science: Whrer Do / Should They Meet in 2011 (and Beyond)? [PDF]
philosophy of science, philosophy of statistics, decision theory, likelihood, subjective probability, Bayesianism, Bayes theorem, Fisher, Neyman and Pearson, Jeffreys, induction, frequentism, reliability ...
Deborah Mayo
core
Bayesian Updating, Model Class Selection and Robust Stochastic Predictions of Structural Response [PDF]
, 2011 A fundamental issue when predicting structural response by using mathematical models is how to treat both modeling and excitation uncertainty. A general framework for this is presented which uses probability as a multi-valued conditional logic for ...
Beck, James L.
core
Scaling‐Aware Rating of Poisson‐Limited Demand Forecasts
Journal of Forecasting, EarlyView.ABSTRACT Forecast quality should be assessed in the context of what is possible in theory and what is reasonable to expect in practice. Often, one can identify an approximate upper bound to a probabilistic forecast's sharpness, which sets a lower, not necessarily achievable, limit to error metrics.
Malte C. Tichy +4 more
wiley +1 more source
Estimation of a closed population size of tadpoles in temporary pond
Brazilian Journal of Biology, 2017 The practice of capture-recapture to estimate the diversity is well known to many animal groups, however this practice in the larval phase of anuran amphibians is incipient.
M. S. C. S. Lima +2 more
doaj +1 more source
UK Forecasts of Annual GDP: Their Accuracy and the Information Categories Underlying Their Revisions
Journal of Forecasting, EarlyView.ABSTRACT Policy makers are concerned with the accuracy of GDP forecasts and want to understand the reasons for the revision of forecasts. We study these issues by examining forecasts of annual UK GDP growth by a panel of agents, published monthly by HM Treasury. We focus on two main issues: the developing accuracy of the group‐mean forecast as horizons
Nigel Meade, Ciaran Driver
wiley +1 more source
Klasifikasi Penyebab Penyalahgunaan Narkoba Dari Berita Online Dengan Menggunakan Naive Bayes
Jurnal ELTIKOM: Jurnal Teknik Elektro, Teknologi Informasi dan Komputer, 2017 This research conducted the classification process by applying the method of classification of Naive Bayes. News article document is one form of text data that is not structured so that requires the process of cleaning data and pre-processing first.
Laili Wahyunita
doaj +1 more source
Journal of Forecasting, EarlyView.ABSTRACT Using online job advertisement data improves the timeliness and granularity depth of analysis in the labor market in domains not covered by official data. Specifically, its variation over time may be used as an anticipator of official employment variations.
Pietro Giorgio Lovaglio +1 more
wiley +1 more source
Equations of States in Statistical Learning for a Nonparametrizable and Regular Case
, 2009 Many learning machines that have hierarchical structure or hidden variables are now being used in information science, artificial intelligence, and bioinformatics.
Watanabe, Sumio
core +1 more source
Income–Well‐Being Gradient in Sickness and Health
Health Economics, EarlyView.ABSTRACT We propose a method for studying the value of insurance. For this purpose, we analyze the well‐being of the same individuals, comparing sick and healthy years, using German panel survey data on life satisfaction. We impose structure on the income–well‐being gradient by fitting a flexible utility function to the data, focusing on the ...
Ohto Kanninen +2 more
wiley +1 more source