Ngboost Alternatives

Similar projects and alternatives to ngboost

PaddlePaddle

6 21,616 10.0 C++ ngboost VS PaddlePaddle

PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice （『飞桨』核心框架，深度学习&机器学习高性能单机、分布式训练和跨平台部署）
lleaves

4 297 6.7 Python ngboost VS lleaves

Compiler for LightGBM gradient-boosted trees, based on LLVM. Speeds up prediction by ≥10x.
InfluxDB

www.influxdata.com sponsored

Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
Keras

78 60,937 9.9 Python ngboost VS Keras

Deep Learning for humans
natural-posterior-network

1 71 0.0 Python ngboost VS natural-posterior-network

Official Implementation of "Natural Posterior Network: Deep Bayesian Predictive Uncertainty for Exponential Family Distributions" (ICLR, 2022)
data-science-ipython-notebooks

1 26,459 0.0 Python ngboost VS data-science-ipython-notebooks

Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
scikit-learn

81 58,130 9.9 Python ngboost VS scikit-learn

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spaCy

106 28,751 9.2 Python ngboost VS spaCy

💫 Industrial-strength Natural Language Processing (NLP) in Python
WorkOS

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The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.

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Exploring Estimations and Confidence Intervals of Three Point Shooting
1 project | /r/NBATalk | 16 Aug 2021

For DARKO, I do this by passing my time-decay/padding/kalman calculations as features (along with other pieces of biographical information) into NGboost. This gives me a point-estimate prediction, as well as confidence intervals. NGboost is somewhat limited in terms of what distributions it can handle, so you need to use care here, but it's very powerful since it can easily work with a large feature space (DARKO uses hundreds of features).