This dataset is a collection of samples related to random forests, a popular machine learning algorithm. Random forests are an ensemble learning method that operate by constructing a multitude of decision trees at training time and outputting the class that is the mode of the classes (classification) or mean prediction (regression) of the individual trees.

Dataset Features

  • Size: Large variety of datasets with different sizes and complexities.
  • Types: Both classification and regression datasets are available.
  • Sources: Data from various domains, including but not limited to finance, healthcare, and social media.

Usage

The dataset can be used for:

  • Research: Understanding the performance of random forests on different types of data.
  • Education: Teaching and learning about machine learning algorithms and ensemble methods.
  • Projects: Building predictive models for various applications.

Example

Here's an example of a dataset entry:

  • Feature: Temperature (°C)
  • Target: Survival (0 for not survived, 1 for survived)

Random Forests Example

Further Reading

For more information on random forests and machine learning, check out our Machine Learning Basics.