NumericEnsembles 0.5.0

NumericEnsembles 0.4.0

NumericEnsembles 0.3.0

NumericEnsembles 0.2.0

NumericEnsembles 0.1.0

NumericEnsembles 1.0.0

Added example of New_Boston data set as a new data set to use in NumericEnsembles (‘do_you_have_new_data?’)

Removed neuralnet models since I could not get the RMSE down, added cppls, which creates a much more accurate ensemble compared to the previous version.

Removed cppls, not reliable on several data sets.

Re-added neuralnet models (individual and ensemble) since I was able to get those to work without error

Added best subsets: Forward, backward, exhaustive and seqrep

Added save_all_plots to automatically save all plots in the user’s choice of one of six graphics formats: eps, jpeg, pdf, png, svg or tiff

Added Variance Inflation Factor. The user is able to set the VIF value, and models are built with VIF values at or below the user’s choice of VIF value

Added “free” and “fixed” scales to all appropriate plots. Each result has two plots, one with free scales, the other with fixed scales.

Added Kolomogrov-Smirnovv test to help the user see which models test similar to the actual holdout data

Added several “Holdout vs train” charts to show how each model performs across multiple resamples, and the range of values of holdout RMSE / train RMSE