CatBoost.jl

Julia wrapper of the python library CatBoost for boosted decision trees
Author beacon-biosignals
Popularity
1 Star
Updated Last
1 Month Ago
Started In
May 2021

CatBoost.jl

Build Status CodeCov

Julia interface to CatBoost.

Setting up PyCall

Please follow the PyCall guidelines described in PyCall.jl.

We highly recommend using a Julia-specific Python environment to handle dependencies. We recommend that users follow the build instructions in Conda.jl.

If users have installed miniconda on their local machine, we recommend checking out the Julia-specific Python environment (which is usually located at $HOME/.julia/conda/3) and installing catboost there with pip:

pip install catboost

Example

module Regression

using CatBoost

train_data = [[1, 4, 5, 6], [4, 5, 6, 7], [30, 40, 50, 60]]
eval_data = [[2, 4, 6, 8], [1, 4, 50, 60]]
train_labels = [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

Used By Packages

No packages found.