Results 251 to 260 of about 2,150,687 (292)
Some of the next articles are maybe not open access.
Examining Predictive Accuracy Among Discounting Models
Journal of Risk and Uncertainty, 2002zbMATH Open Web Interface contents unavailable due to conflicting licenses.
KELLER L. R., STRAZZERA, ELISABETTA
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2020
In this chapter, support vector machines (SVM) are introduced - a kind of classifiers developed specifically to achieve high predictive accuracy. First, the basic variant for binary classification into linearly separable classes is presented, which is then followed by extensions to non-linear classification, multiple classes and noise-tolerant ...
Martin Holeňa, Petr Pulc, Martin Kopp
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In this chapter, support vector machines (SVM) are introduced - a kind of classifiers developed specifically to achieve high predictive accuracy. First, the basic variant for binary classification into linearly separable classes is presented, which is then followed by extensions to non-linear classification, multiple classes and noise-tolerant ...
Martin Holeňa, Petr Pulc, Martin Kopp
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Prognostic Accuracy of Delirium Prediction Models
AJN, American Journal of Nursing, 2023According to this study: The prognostic accuracy of models used to predict delirium in patients admitted to the ICU varies.The PRE-DELIRIC model performs best and can be used in both patients receiving and not receiving mechanical ventilation.
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Predictive accuracy and explained variation
Statistics in Medicine, 2003AbstractMeasures of the predictive accuracy of regression models quantify the extent to which covariates determine an individual outcome. Explained variation measures the relative gains in predictive accuracy when prediction based on covariates replaces unconditional prediction.
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Robust tests of predictive accuracy [PDF]
We propose robust counterparts to tests of equal forecast accuracy such as those proposed by Diebold and Mariano (1995) and West (1996). We illustrate the robustness problem and evaluate the size and the power properties of the classical and robust tests under various types of deviations from model assumptions.
Dell'Aquila, Rosario, Ronchetti, Elvezio
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Human Neuroelectric Patterns Predict Performance Accuracy
Science, 1987In seven right-handed adults, the brain electrical patterns before accurate performance differed from the patterns before inaccurate performance. Activity overlying the left frontal cortex and the motor and parietal cortices contralateral to the performing hand preceded accurate left- or right-hand performance.
A S, Gevins +8 more
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Nonparametric Predictive Inference for diagnostic accuracy
Journal of Statistical Planning and Inference, 2012zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Coolen-Maturi, Tahani +2 more
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Quantifying predictive accuracy in survival models
Journal of Nuclear Cardiology, 2017For time-to-event outcomes in medical research, survival models are the most appropriate to use. Unlike logistic regression models, quantifying the predictive accuracy of these models is not a trivial task. We present the classes of concordance (C) statistics and R 2 statistics often used to assess the predictive ability of these models. The discussion
Seth T, Lirette, Inmaculada, Aban
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Synthese, 1975
This paper, I am sorry to say, is deeply sceptical. It is also rather technical. And the scepticalities, I fear, are no easier to renounce than are the techni calities. The paper presents an elementary mathematical result that appears to impinge negatively on any reasonable theory of knowledge with empiricist pretensions.
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This paper, I am sorry to say, is deeply sceptical. It is also rather technical. And the scepticalities, I fear, are no easier to renounce than are the techni calities. The paper presents an elementary mathematical result that appears to impinge negatively on any reasonable theory of knowledge with empiricist pretensions.
openaire +1 more source
Beyond rating prediction accuracy
Proceedings of the 7th ACM conference on Recommender systems, 2013This paper proposes a number of studies in order to move recommender systems beyond the traditional paradigm and the classical perspective of rating prediction accuracy. We contribute to existing helpful but less explored paradigms and also propose new approaches aiming at more useful recommendations for both users and businesses.
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