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Some form of feature selection will improve classification results and improve the efficiency of the system.
Usually, some form of feature (gene) selection is adopted in the formation of the prediction rule.
A Bernoulli NB classifier requires some form of feature selection or else its accuracy will be low.
The network has previous in reviving series in the form of feature films, releasing two Sex and the City spin-off movies in 2008 and 2010, and an Entourage film earlier this year.
Many classification problems involve features whose specificity demand some form of feature space transformation (preprocessing) coupled with post-processing consensus analysis in order to accomplish a successful discrimination between different classes.
The previous state-of-the-art systems required large amounts of task-specific knowledge in the form of feature engineering, lexicons and data pre-processing to achieve high performance.
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This paper deals with the problem of extracting information from non-stationary signals in the form of features that can be used for effective decision-making in both data analysis and machine learning for automatic classification systems.
The first instantiation of the model describes a form of feature-based attention and yields STRF adaptation patterns consistent with a contrast matched filter previously reported in neurophysiological studies.
The first approach operates at the front-end via the exploration of discriminative information in speech in the form of features (e.g., voice source, spectro-temporal, prosodic, high-level) [1]-[6].
Some form of feature-based attention (Moran & Desimone, 1985; Saenz et al., 2002, 2003; Reynolds & Chelazzi, 2004; Hayden & Gallant, 2005; Maunsell & Treue, 2006; Serences & Boynton, 2007) combined with perceptual learning (Gilbert & Sigman, 2007) may explain the additional relationship between neural responses and behavior.
In contrast, our proposed approach is inductive, and can integrate multiple diverse sources of data in the form of features, including the different biological networks.
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variation of feature
formation of feature
form of characteristic
form of film
form of featured
form of films
form of features
form of carbon
form of communicating
form of engagement
form of dementia
form of banishment
form of consent
form of acceptance
form of documentary
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form of coercion
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form of dyslexia
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