LightGBM is a powerful gradient boosting framework.
Requirements
-
LightGBM (Ruby binding)
-
lib_lightgbm.so
,lib_lightgbm.dylib
,lib_lightgbm.dll
are included in Gem.
-
-
Red Datasets
- MNIST datasets.
gem install red-datasets
gem install lightgbm
Run
require 'lightgbm'
require 'datasets'
train_mnist = Datasets::MNIST.new(type: :train)
test_mnist = Datasets::MNIST.new(type: :test)
train_x = train_mnist.map(&:pixels)
train_y = train_mnist.map(&:label)
test_x = test_mnist.map(&:pixels)
test_y = test_mnist.map(&:label)
params = {
task: :train,
boosting_type: :gbdt,
objective: :multiclass,
num_class: 10
}
train_set = LightGBM::Dataset.new(train_x, label: train_y)
booster = LightGBM.train(params, train_set)
result = booster.predict(test_x)
result.map! { |i| i.index(i.max) }
accuracy = test_y.zip(result).count { |i, j| i == j } / test_y.size.to_f
puts accuracy
0.9727
Good! 🌟
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