Saving models to disk

JLD.jl is the preferred way of saving ScikitLearn.jl models. If you also use Python models (via @sk_import), you will have to import PyCallJLD as well.

using ScikitLearn
using ScikitLearn.Pipelines
using PyCall, JLD, PyCallJLD

@sk_import decomposition: PCA
@sk_import linear_model: LinearRegression

pca = PCA()
lm = LinearRegression()

pip = Pipeline([("PCA", pca), ("LinearRegression", lm)])
fit!(pip, ...)   # fit to some dataset"pipeline.jld", "pip", pip)

# Load back the pipeline
pip = JLD.load("pipeline.jld", "pip")