Is the Averager documentation deprecated?

[era127]

In the documentation for Static transformers the example for the Averager uses @from_network but when I run that example it indicates that the way the code deprecated. Is the code in that example deprecated?

I'm just starting to look at MLJ and I'm interested in making a network that averages an array of continuous regression models. Alternatively is it possible to use stack but with a metalearner that just is average instead of a linear model?

X = source()
y = source() 

ridge = (@load RidgeRegressor pkg=MultivariateStats)()
knn = (@load KNNRegressor)()
averager = Averager(0.5)

hotM = machine(OneHotEncoder(), X)
W = transform(hotM, X) # one-hot encode the input

ridgeM = machine(ridge, W, y)
y1 = predict(ridgeM, W)

knnM = machine(knn, W, y)
y2 = predict(knnM, W)

averagerM= machine(averager)
yhat = transform(averagerM, y1, y2)

learning_mach = machine(Deterministic(), X, y; predict=yhat)

@from_network learning_mach struct DoubleRegressor
       regressor1=ridge
       regressor2=knn
       averager=averager
       end

┌ Warning: Learning network machines are deprecated. For the recommended way of exporting learning networks as new stand-alone model types, see the "Learning Networks" section of the MLJ manual. 

[ablaom]

Yes, you are right, @rdavis120, the example is out of date. Thanks for pointing this out.

You can find an update to the example here.

Alternatively is it possible to use stack but with a metalearner that just is average instead of a linear model?

That won't work. The metalearner needs to be supervised model.

[ablaom]

Closed in favour of #1040.