Machine learning toolbox
The Shogun Machine learning toolbox provides a wide range of unified and efficient Machine Learning (ML) methods. The toolbox seamlessly combines multiple data representations, algorithm classes, and general purpose tools. This enables both rapid prototyping of data pipelines and extensibility in terms of new algorithms.
System | Target | Derivation | Build status |
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x86_64-linux | /gnu/store/p3klkb9nan74rynp4f1hnvfmz8pa3z0g-shogun-6.1.3.drv |
Linter | Message | Location |
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input-labels Identify input labels that do not match package names | label 'numpy' does not match package name 'python-numpy' | |
input-labels Identify input labels that do not match package names | label 'octave' does not match package name 'octave-cli' | |
input-labels Identify input labels that do not match package names | label 'arpack' does not match package name 'arpack-ng' | |
inputs-should-be-native Identify inputs that should be native inputs | 'swig' should probably be a native input | |
formatting Look for formatting issues in the source | line 675 is way too long (91 characters) |