Skip to main content

tune with optuna and model

Project description

trainme - documentation

Authors

kaggle-autolgb

trainer is a combination of xgboost, lightgbm and optuna. I tried to make kaggle monthly competition simple. Its only working with classification problem.

Installation

pip install trainer

Features

  • autotune
  • autotrain
  • auto submission file generate
  • auto prediction

Deployment

from src.read_data import ReadFile

s = ReadFile(
	train_path="/home/aditta/Desktop/trainme/trainme/input/multi_class_classification.csv",
	test_path="/home/aditta/Desktop/trainme/trainme/input/multi_class_classification_test.csv",
	label="target",
    	task_type="multi_classification",
	compare=False,
	fold="skfold",
	model_name="xgb",
	output_path="/media/aditta/NewVolume/amazon",
	study_name="new_train",
	store_file ="out9",
	n_trials=1
)

print(s.report())
print(s.train())

License

Apache 2.0

Project details


Release history Release notifications | RSS feed

This version

1.0

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

trainme-1.0.tar.gz (10.6 kB view hashes)

Uploaded Source

Built Distribution

trainme-1.0-py3-none-any.whl (16.4 kB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page