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.
“@Hannah I just noticed we don't have entry for algo parameter {{autoencoder}} - when I search "autoencoder" in our documentation it shows up results but nothing an uniformed user would probably click on. should we have some kind of list of algos that includes algos withing algos? like for example autoencoder in deep learning or HGLM in GLM”
“@Hannah I just noticed we don't have entry for algo parameter {{autoencoder}} - when I search "autoencoder" in our documentation it shows up results but nothing an uniformed user would probably click on. should we have some kind of list of algos that includes algos withing algos? like for example autoencoder in deep learning or HGLM in GLM”
“We could put a list on the [algo intro page|https://docs.h2o.ai/h2o/latest-stable/h2o-docs/data-science.html] and link to sections that expand on the information for each “matryoshka” algorithm. Or maybe add it to the general [Algorithm FAQ|https://docs.h2o.ai/h2o/latest-stable/h2o-docs/faq/algorithms.html]. We should probably add an {{autoencoder}} algo-param page, though. Doesn’t need to be super in-depth, but having an easy-access example would be nice.”