Results 281 to 290 of about 127,481 (314)
Predictive uncertainty in environmental modelling
Neural Networks, 2007 Artificial neural networks have proved an attractive approach to non-linear regression problems arising in environmental modelling, such as statistical downscaling, short-term forecasting of atmospheric pollutant concentrations and rainfall run-off ...
Cawley, Gavin C. +3 more
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Connection Science, 2009
Modelling long-term dependencies in time series has proved very difficult to achieve with traditional machine-learning methods. This problem occurs when considering music data. In this paper, we introduce predictive models for melodies. We decompose melodic modelling into two subtasks.
Paiement, Jean-François +2 more
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Modelling long-term dependencies in time series has proved very difficult to achieve with traditional machine-learning methods. This problem occurs when considering music data. In this paper, we introduce predictive models for melodies. We decompose melodic modelling into two subtasks.
Paiement, Jean-François +2 more
openaire +1 more source
Approaches to predictive modeling
The Annals of Thoracic Surgery, 1994A four-component clinical model for process improvement is presented: (1) patient-related risk factors, (2) clinical processes ordered by the attending physician, (3) the hospital's execution of the physician's plan, and (4) the patient's outcome, or outcomes, resulting from the first three factors.
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Model Assessment for Predictive Classification Models
Communications in Statistics - Theory and Methods, 2010In this article, we present a novel methodology to assess predictive models for a binary target. In our opinion, the main weakness of the criteria proposed in the literature is not to take the financial costs of a wrong decision into account. The objective of this article is to derive the optimal cut-off in predictive classification models and to ...
UBERTI, PIERPAOLO, Figini S.
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Models for Prediction Purposes
Journal of Mental Science, 1959It is natural for psychiatrists and others dealing with mental patients to enquire what the prognosis is for a patient showing certain symptoms or syndromes of symptoms—taking age and the history of the patient's illness into account. The very fact that the symptoms generally form syndromes points to their interdependence to a greater or lesser degree,
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A prediction model for bovine ostertagiasis
Veterinary Record, 1979A mathematical model based on development and mortality rates, and incorporating data on the infectivity, fecundity and migratory behaviour of Ostertagia ostertagi, was used to predict the level of pasture contamination and the occurrence of clinical ostertagiasis in grazing calves during 1975 and 1976. A comparison of the predicted and observed events
Gettinby, G. +3 more
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A Model For Prediction Of Endometrial Cancer
Acta Obstetricia et Gynecologica Scandinavica, 1989An epidemiological statistical model was designed to identify women at low and high risk of developing endometrial cancer (EC). The model was based on a number of easily identified clinical factors such as hirsutism, parity, diabetes mellitus, body mass index (BMI) and smoking.
E, Dahlgren +4 more
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Applications of Prediction Models
2008In this chapter, we consider several areas of application of prediction models in public health, clinical practice, and medical research. We use several small case studies for illustration.
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Structure prediction and modelling
Current Biology, 1992Cracking the second fundamental code of molecular biology (how the tertiary structure of a protein is determined by its amino acid sequence) remains an elusive goal. However, the impetus to establish credible approximations, if not a definitive solution to this relationship, has never been greater.
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Modeling and Prediction of Human Behavior
Neural Computation, 1999We propose that many human behaviors can be accurately described as a set of dynamic models (e.g., Kalman filters) sequenced together by a Markov chain. We then use these dynamic Markov models to recognize human behaviors from sensory data and to predict human behaviors over a few seconds time. To test the power of this modeling approach, we report an
Alex Pentland, Andrew Liu
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