[jdonaldson]

We provide basic classification and regression trees for now, and we can decide which one is appropriate from the objective field type. Once we start adding in other types of models we will add a model type parameter for the relevant API method.

[shoo]

Do you plan on exposing parameters that control the fitting process? E.g. loss function / tree depth / min samples per leaf? Or will the fitting process always be a black-box automagic call with no user-controllable knobs?

Is there any plan to provide some assessment of model accuracy via the API - e.g. K-fold cross validation with respect to some specified loss function?

[jdonaldson]

We do a little automagic currently, but we'll expose some of the knobs soon, probably first via the API. Expressing model confidence and handling loss functions are being worked on right now.

Did I mention we're hiring? Someone with the right combination of big data and machine learning skills can make a big impact. https://bigml.com/team