It is just a workaround to fix the current ngboost package issue. See: https://github.com/stanfordmlgroup/ngboost/issues/283
Project description
NGBoost: Natural Gradient Boosting for Probabilistic Prediction
ngboost is a Python library that implements Natural Gradient Boosting, as described in "NGBoost: Natural Gradient Boosting for Probabilistic Prediction". It is built on top of Scikit-Learn, and is designed to be scalable and modular with respect to choice of proper scoring rule, distribution, and base learner. A didactic introduction to the methodology underlying NGBoost is available in this slide deck.
Installation
via pip
pip install --upgrade ngboost
via conda-forge
conda install -c conda-forge ngboost
Usage
Probabilistic regression example on the Boston housing dataset:
from ngboost import NGBRegressor
from sklearn.datasets import load_boston
from sklearn.model_selection import train_test_split
from sklearn.metrics import mean_squared_error
X, Y = load_boston(True)
X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=0.2)
ngb = NGBRegressor().fit(X_train, Y_train)
Y_preds = ngb.predict(X_test)
Y_dists = ngb.pred_dist(X_test)
# test Mean Squared Error
test_MSE = mean_squared_error(Y_preds, Y_test)
print('Test MSE', test_MSE)
# test Negative Log Likelihood
test_NLL = -Y_dists.logpdf(Y_test).mean()
print('Test NLL', test_NLL)
Details on available distributions, scoring rules, learners, tuning, and model interpretation are available in our user guide, which also includes numerous usage examples and information on how to add new distributions or scores to NGBoost.
License
Reference
Tony Duan, Anand Avati, Daisy Yi Ding, Khanh K. Thai, Sanjay Basu, Andrew Y. Ng, Alejandro Schuler. 2019. NGBoost: Natural Gradient Boosting for Probabilistic Prediction. arXiv
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file ngboost-release-0.3.12.post2.tar.gz
.
File metadata
- Download URL: ngboost-release-0.3.12.post2.tar.gz
- Upload date:
- Size: 25.7 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: poetry/1.1.15 CPython/3.10.6 Linux/5.15.0-47-generic
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 8b50c3c1fe4598cd909667be9960970092f3448545151a33c671fa00b1fe76a0 |
|
MD5 | 4963160a390ce192e9cad7d82be38964 |
|
BLAKE2b-256 | fb5c81649866e0ed780965dd8e21e4de5dbcccc077606b52138b149d2411156b |
File details
Details for the file ngboost_release-0.3.12.post2-py3-none-any.whl
.
File metadata
- Download URL: ngboost_release-0.3.12.post2-py3-none-any.whl
- Upload date:
- Size: 31.9 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: poetry/1.1.15 CPython/3.10.6 Linux/5.15.0-47-generic
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | e05723e315f36eff6d68b2f3a574e8e7d66207958a6e6b669da6d76984b26404 |
|
MD5 | 774803a27668e1303ae34f9556c98944 |
|
BLAKE2b-256 | 08e36de0f102e0003c184d26d44cce20c4d41b7288010b6961b539ea1eddacd0 |