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1 Φεβ 2021 · DF21 is an implementation of Deep Forest 2021.2.1. It is designed to have the following advantages: Powerful: Better accuracy than existing tree-based ensemble methods. Easy to Use: Less efforts on tunning parameters. Efficient: Fast training speed and high efficiency. Scalable: Capable of handling large-scale data.
- Installation Guide
Installation Guide ¶. Stable Version ¶. The stable version...
- API Reference
Note. Deep forest supports two kinds of modes for training:...
- Experiments
With the number of input dimensions increasing (e.g., on...
- Contributors
This project follows the all-contributors specification....
- Changelog
Badge. Meaning. Feature. Add something that cannot be...
- Report From Users
Report from Users¶. The page collects user reports on using...
- Related Software
Deep Forest (DF21) » Related Software; Edit on GitHub;...
- Parameters Tunning
This page contains parameters tuning guides for deep forest....
- Installation Guide
How to Get Started ¶. This is a quick start guide for you to try out deep forest. The full script is available at Example. Installation ¶. The package is available via PyPI. As a kind reminder, do not forget the hyphen (-) between deep and forest. $ pip install deep-forest. Load Data ¶.
pip install DeepForest. DeepForest itself is pure Python and will work on all major operating systems, but has spatial and deep learning dependencies that can be harder to install, particularly on Windows. To make this easier DeepForest can also be installed using conda and mamba.
1 Φεβ 2021 · DF21 is an implementation of Deep Forest 2021.2.1. It is designed to have the following advantages: Powerful: Better accuracy than existing tree-based ensemble methods. Easy to Use: Less efforts on tunning parameters. Efficient: Fast training speed and high efficiency. Scalable: Capable of handling large-scale data.
Installation Guide ¶. Stable Version ¶. The stable version is available via using: $ pip install deep-forest. The package is portable and with very few package dependencies. It is recommended to use the package environment from since it already installs all required packages.
DF21 is an implementation of Deep Forest 2021.2.1. It is designed to have the following advantages: Powerful: Better accuracy than existing tree-based ensemble methods. Easy to Use: Less efforts on tunning parameters. Efficient: Fast training speed and high efficiency. Scalable: Capable of handling large-scale data.
DeepForest is a python package for training and predicting ecological objects in airborne imagery. DeepForest currently comes with a tree crown object detection model and a bird detection model. Both are single class modules that can be extended to species classification based on new data.
