CatBoost.jl

Julia wrapper of the python library CatBoost for boosted decision trees
Author JuliaAI
Popularity
11 Stars
Updated Last
3 Months Ago
Started In
May 2021

CatBoost.jl

Build Status CodeCov

Julia interface to CatBoost. This library is a wrapper CatBoost's Python package via PythonCall.jl.

For a nice introduction to the package, see the examples.

Installation

This package is available in the Julia General Registry. You can install it with either of the following commands:

pkg> add CatBoost
julia> using Pkg; Pkg.add("CatBoost")

Example

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

MLJ Example

module Regression

using CatBoost.MLJCatBoostInterface
using DataFrames
using MLJBase

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

# Initialize CatBoostClassifier
model = CatBoostRegressor(; iterations=2, learning_rate=1.0, depth=2)
mach = machine(model, train_data, train_labels)

# Fit model
MLJBase.fit!(mach)

# Get predictions
preds_class = MLJBase.predict(mach, eval_data)

end # module

Restricting Python catboost version

By default, CatBoost.jl installs the latest compatible version of catboost (version >=1.1) in your current CondaPkg.jl environment. To install a specific version, create a CondaPkg.toml file using CondaPkg.jl. Below is an example for specifying catboost version v1.1:

using CondaPkg
CondaPkg.add("catboost"; version="=1.1")

This will create a CondaPkg.toml file in your current envrionment with the restricted catboost version. For more information on managing Conda environments with CondaPkg.jl, refer to the official documentation.

Used By Packages

No packages found.