CatBoost.jl

module Regression

using CatBoost
using PythonCall

train_data = PyList([[1, 4, 5, 6], [4, 5, 6, 7], [30, 40, 50, 60]])
eval_data = PyList([[2, 4, 6, 8], [1, 4, 50, 60]])
train_labels = PyList([10, 20, 30])

# Initialize CatBoostRegressor
model = CatBoostRegressor(iterations = 2, learning_rate = 1, depth = 2)

# Fit model
fit!(model, train_data, train_labels)

# Get predictions
preds = predict(model, eval_data)

end # module

module Regression

using CatBoost
using DataFrames
using MLJBase

train_data = DataFrame([[1,4,30], [4,5,40], [5,6,50], [6,7,60]], :auto)
eval_data = DataFrame([[2,1], [4,4], [6,50], [8,60]], :auto)
train_labels = [10.0, 20.0, 30.0] 

# Initialize MLJ Machine
model = CatBoostRegressor(iterations = 2, learning_rate = 1, depth = 2)
mach = machine(model, train_data, train_labels)

# Fit model
MLJBase.fit!(mach)

# Get predictions
preds = predict(model, eval_data)

end # module