[D] What are your favorite Random Forest implementations that support categoricals

• catboost

  8 7,753 9.9 Python

  A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

  

If you considering GBDT check out catboost, unfortunately RF mode is not available but library implement lots of interesting categorical encoding tricks that boost accuracy.

• DALEX

  2 1,326 5.9 Python

  moDel Agnostic Language for Exploration and eXplanation

  

There are a couple of ways to use Shapley values for explanations in R. One way is to use DALEX, which also contains a lot of other methods besides SHAP. Another one is iml. I am sure there are several other implementations of SHAP as well.

• InfluxDB

  www.influxdata.com featured

  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.

  

Suggest a related project