Examples of using Variable selection in English and their translations into Spanish
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Variable selection on the found data.
Stepwise Regression Variable selection using stepwise regression.
Variable Selection and Discriminant Analysis.
Five methods are shown for the variable selection split in two groups.
Variable selection and implementation for easier integration in SW application Rooftop.
Added ability to enable built-in variables on the fly in variable selection menus.
A learning algorithm takes advantage of its own variable selection process and performs feature selection and classification simultaneously.
The chapter will describe didactically alternative parametric, semi-parametric andnon-parametric approaches to variable selection and model selection. .
Accessories- Multi connection to EDS or EDS-3G- Individual variable selection- Database migration to SQL- Installation on PCs with Windows.
The chapter will present what is usually referred to as the automatic leading indicators(ALI) approach andwill detail the purpose of the indicator, the variable selection and the estimation phases.
In particular, it will present the variable selection approaches and algorithms(e.g., least-angle regression(LARS)) as well as alternative regression models based on bridge regression or factor regression.
It offers opulent living accommodations on three separate decks providing the owners and their guests with a widely variable selection of living and entertaining environments.
In the second part, the chapter will present variable selection techniques, which can be useful when there is a need to reduce the dimensions of the variable space and/or to identify the most appropriate variable or combination of variables to be used.
It should clearly outline the justification for the choice of the reference cycle and explain the variable selection approach followed, as well as the de-trending methods and the aggregation scheme.
In machine learning and statistics, feature selection, also known as variable selection, attribute selection or variable subset selection, is the process of selecting a subset of relevant features(variables, predictors) for use in model construction.
The chapter will discuss the construction of turning points indicators for different kind of cycles,mainly focusing on: identification of an appropriate dataset; variable selection techniques; model selection; model estimation; and evaluation criteria of the indicators.
It will describe clearly the justification for the choice of the reference cycle, the approach to variable selection, the aggregation scheme, etc. This chapter will also present the main similarities to and the differences from the original NBER approach and examine the latest changes and enhancements proposed after the global economic and financial crisis.
Different aspects of validation of QSAR models that need attention include methods of selection of training set compounds, setting training set size and impact of variable selection for training set models for determining the quality of prediction.
In statistics and machine learning, lasso(least absolute shrinkage and selection operator; also Lasso or LASSO)is a regression analysis method that performs both variable selection and regularization in order to enhance the prediction accuracy and interpretability of the statistical model it produces.
Chapter 5: Variables selection approaches, the information set structure and various typologies of rapid estimates.
Variable temperature selection system from 20°C to 100°C.
Common religion is the selection variable in the first stage estimation.
Variable speed selection for ideal speed to any material.
Selection between variable or classic ink key keyboards.
Variable speed selection from 490- 2100 RPM for all applications.
All of the information about the currently selected layers is contained inside the selection variable.