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The reason behind better performance of the model developed by us is mainly because we have used a statistical learning method which generates prediction models by learning from large complex datasets, also taking care of over-fitting problem.
We used a statistical learning framework to evaluate the ability of three machine-learning methods to predict nitrate concentration in shallow groundwater of the Central Valley, California: boosted regression trees (BRT), artificial neural networks (ANN), and Bayesian networks (BN).
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This paper presents the results from the analysis of simulated chemical mixtures using a statistical learning method called gradient boosted regression trees (hereafter called boosted CARTs).
In fact, we are quite concerned that database screening, done using a predictor derived from a statistical learning algorithm, is subject to procedural demands that may be difficult to maintain.
We performed an exploratory analysis using a multivariate statistical learning technique known as support vector machine; this, however, did not yield any significant findings, suggesting that group-level differences do not necessarily allow accurate inferences at the level of the individual disorder.
Concerning the first step of word extraction from speech, when no semantic or prosodic information is available, it has been suggested that listeners can use a general statistical learning mechanism to segment speech based on adjacent [2] and non-adjacent statistical dependencies between syllables [11].
In this study, we demonstrate that a statistical learning approach using three features or material descriptors related to the chemical bonding and atomic radii of the elements in the alloys, provides a means to predict transformation temperatures.
Recently, Tan and colleagues tackled this question by using a statistical technique called "machine learning" to predict which children will gain the best language skills within 2 years of implantation.
Motion patterns are then learned using a statistical model applied to the vector space.
Instead, we must use a statistical classifier based on supervised machine learning, where the model is fitted and evaluated by iterative training and testing on independent, randomly selected subsets of the data.
Learning how to use a statistical package is important.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com