H2O modeling capabilities
H2O's supervised learning algorithms are used to train models on training data, tune them on validation data, and score or predict with them on test or live production data. H2O has extensive capabilities to train, evaluate, explain, score, and inspect models. These are summarized in the following diagram:
Figure 4.3 – The H2O supervised learning capabilities
Let's take a closer look at the model training capabilities.
H2O model training capabilities
Algorithms are at the heart of model training, but there are a larger set of capabilities to consider beyond the algorithms themselves. H2O provides the following model training capabilities:
- AutoML: An easy-to-use interface and parameter set that automates the process of training and tuning many different models, using multiple algorithms, to create a large number of models in a short amount of time.
- Cross-validation: K-fold validation is used to generate...
