there are pre-processing or sampling steps not contained in the package or you just donвЂ™t like the way the package does things.

you would like to run an existing model in the package your own way.

you are testing out a novel model or the package doesnвЂ™t have a model that you are interested in.

However, you may want to create your own because: The package contains a large number of predictive model interfaces.

22.2 Internal and External Performance Estimates.

22 Feature Selection using Simulated Annealing.

21.2 Internal and External Performance Estimates.

21 Feature Selection using Genetic Algorithms.

20.3 Recursive Feature Elimination via caret.

20.2 Resampling and External Validation.

19 Feature Selection using Univariate Filters.

18.1 Models with Built-In Feature Selection.

16.6 Neural Networks with a Principal Component Step.

16.2 Partial Least Squares Discriminant Analysis.

16.1 Yet Another k-Nearest Neighbor Function.

13.9 Illustrative Example 6: Offsets in Generalized Linear Models.

13.8 Illustrative Example 5: Optimizing probability thresholds for class imbalances.

13.7 Illustrative Example 4: PLS Feature Extraction Pre-Processing.

13.6 Illustrative Example 3: Nonstandard Formulas.

13.5 Illustrative Example 2: Something More Complicated - LogitBoost.

13.2 Illustrative Example 1: SVMs with Laplacian Kernels.

12.1.2 Using additional data to measure performance.

12.1.1 More versatile tools for preprocessing data.

11.4 Using Custom Subsampling Techniques.7.0.27 Multivariate Adaptive Regression Splines.5.9 Fitting Models Without Parameter Tuning.5.8 Exploring and Comparing Resampling Distributions.5.7 Extracting Predictions and Class Probabilities.5.1 Model Training and Parameter Tuning.4.4 Simple Splitting with Important Groups.4.1 Simple Splitting Based on the Outcome.3.2 Zero- and Near Zero-Variance Predictors.The load capacity of your unit is designated by weight, not by volume, so you cannot necessarily use all available space when loading your unit. A label identifying the unloaded vehicle weight of the actual unit and the cargo carrying capacity is applied to every Forest River RV prior to leaving our facilities. **Estimated Average based on standard build optional equipment.Д®ach Forest River RV is weighed at the manufacturing facility prior to shipping. Available CCC should accommodate fresh potable water (8.3 lbs per gallon).Д«efore filling the fresh water tank, empty the black and gray tanks to provide for more cargo capacity.

*Estimated Average based on standard build optional equipment.Д¬CC (Cargo Carrying Capacity)** - is the amount of weight available for fresh potable water, cargo, additional optional equipment and accessories.Д¬CC is equal to GVWR minus UVW. The UVW does not include cargo, fresh potable water, additional optional equipment or dealer installed accessories. It includes all weight at the unitвЂ™s axle(s) and tongue or pin and LP Gas. UVW (Unloaded Vehicle Weight)*- is the typical weight of the unit as manufactured at the factory. GAWR (Gross Axle Weight Rating) вЂ“ is the maximum permissible weight, including cargo, fluids, optional equipment and accessories that can be safely supported by a combination of all axles.

The forest mods models