startml version 0.1.3

Added deep learning grid search to, feature and weak learner prediction mixing, and PCA for weak learner predictions to ensemble function.

First fully functional workflow on regression models:
startml ->plot -> trim -> plot -> ensemble -> plot -> plot_dlayer

In just a few commands, hundreds of models can be build, inspected or compared, selected, a hyper parameter ensemble search, visually compare ensemble and weak learners, and visualize the layers of of the deep learning ensemble.

Running startml for 40 minutes total building deep learning and gradient boosted machines (20 minutes each) feed into an ensemble with the deep learning algorithm grid search for 200 seconds, keep_features = TRUE, and PCA dimension reduction of 70% scores in top 25 percent of kaggle Ames housing prices "for fun" contest.