Flow: add visualization of model metrics for random grid search

h2oai / h2o-3

H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

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There's a TwoDimTable that has metrics for all the models in a grid. Allow the user to plot any of these metric columns against the model number.

The list of models is always sorted by whatever metric the user asked for, or AUTO: classification ? StoppingMetric.logloss : StoppingMetric.deviance.

The chart should default to the AUTO metric, but allow the user to select whichever metric they like, using a dropdown.

Note that the models are returned best-first, so to get n understandable plot the list should be reversed. This will make the errors decrease left to right.

h2oai / h2o-3

Flow: add visualization of model metrics for random grid search #9654