A random forest is a supervised algorithm that uses an ensemble learning method consisting of a multitude of decision trees, the output of which is the consensus of the best answer to the problem. Random forest can be used for classification or regression.
Related resources
- DLI course: Modeling Time-Series Data with Recurrent Neural Networks in Keras
- GTC session: XGBoost is All You Need
- GTC session: Reducing the Cost of your Data Science Workloads on the Cloud
- GTC session: How AI Will Decode Biology to Radically Improve Lives
- SDK: RAPIDS Accelerator for Spark
- SDK: FME
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