startml version 0.1.2

The plot function has been updated to include test performance of models, and plot an ensemble if it exists in mlblob.

Additionally a function was added called trim which can select model based on correlation and/or performance thresholds after a mlblob is created. This allows for a iterative and more flexible workflow.

An ensemble function was added which creates an ensemble model from an mlblob object. Currently only mean of weak learners is implemented. Planned options include deeplearning, tree methods for meta learners, dimensional reduction, and feature / weak learner predictions mixing.