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Implementation of Random subwindows and Extra-Trees algorithm.

Project description

# pyxit

This code implements the core algorithms for Random subwindows extraction and Extra-Trees classifiers. It is used by Cytomine DataMining applications: classification_validation, classification_model_builder, classification_prediction, segmentation_model_builder and segmentation_prediction. But it can be run without Cytomine on local data (using dir_ls and dir_ts arguments).

It is based on the following paper:

1) For image/object classification: “Towards Generic Image Classification using Tree-based Learning: an Extensive Empirical Study”. Raphael Maree, Pierre Geurts, Louis Wehenkel. Pattern Recognition Letters, DOI: 10.1016/j.patrec.2016.01.006, 2016.

2) For image semantic segmentation: Fast Multi-Class Image Annotation with Random Subwindows and Multiple Output Randomized Trees Dumont et al., 2009 http://orbi.ulg.ac.be/handle/2268/12205

# Install Simply: ` pip install pyxit `

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