Sentence examples for classifications to predict the from inspiring English sources
The objective of this study was to compare the ability of both classifications to predict the number of future (total and severe) exacerbations and mortality in a different patient population, and to add an outcome measure to the comparison: lung function decline.
They used support vector classification to predict the damage location.
In addition, using a large cohort of patients with idiopathic TMA, we emphasized that a pathophysiology-based classification is likely to be more relevant than a clinical presentation-based classification to predict the short term outcome.
Prominent spectral features, such as neutral loss of precursor ions, neutral loss of fragment ions, and intensity of b or y ion series, are incorporated to calculate a probability score using a support vector machine binary classification to predict the validity of the phosphopeptide identification.
We then combined these data with conservative estimates for particle picking, CTF estimation, particle extraction, 2D and 3D classification to predict the overall cost of structure determination on Amazon's EC2 (Supplementary file 2B).
However, we additionally divided the intermediate NPI group into an intermediate low group (3.4classification to predict the outcome of the IDC patients.
Machine learning methods were used to develop predictive models for a classification task, to predict the probability of ICU discharge the day after surgery (further referred to as 'second day of discharge prediction'), and for a regression task, to predict the day of ICU dischargeas a discrete variable (further referred to as 'day of discharge prediction').
The goal of pattern classification is to predict the category of the input data using its attributes.
We propose the use of a classification process to predict the user intention following the previous equation.
We apply our classification model to predict the aquatic toxicity of 3M compounds in the MMsINC database [5].
The goal of classification is to predict the discrete type of output values whereas estimation is aimed at finding the continuous type of output values.
