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These empirical equations have been mostly constructed in some ways by leveraging regression procedures on experimental data, usually laboratory observations (thus from small/medium scale experiments).
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For both learning and generalization, the system leverages regression techniques which allow to infer the motor policy parameters corresponding to a given novel parameterized task, and based on the previously learnt correspondences between policy and task parameters.
The main idea underlying AdOr is to leverage an adaptive regression model to estimate the diversity of a subset and utilize the overlap in a sequence of queries (such as the one shown in Fig. 1) in order to minimize the computational cost incurred in diversifying each query result set.
We also excluded participants who reported fasting times > 24 hr (1%) to reduce regression leverage of these fasting time outliers.
Such studies will tend to report both high rates of EPPs and high mutation rates, creating outlier points with high leverage on the regression.
Then, the algorithm combines a number of these models into an ensemble model leveraging the decision tree regression properties.
We employed an implementation of our previously described model [37] that uses logistic regression and leverages data across HLA alleles to predict CTL epitopes (http://atom.research.microsoft.com/hlabinding/hlabinding.aspx).aspx
Leverage plots and partial regression plots were examined to assess any influence individual observations might have on model coefficients.
Robust methods to detect outliers especially high leverage points for logistic regression models are available in popular statistical software packages [ 22- 24].
This engine is leveraging different machine learning and regression methods to realize the LTE KPI prediction functionality.
ACES leverages a weighted least squares regression to fit a polynomial through points computed on the volume-of-fluid representation of the gas liquid interface.
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