C.6: DeepLIFT: Difference between revisions
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• '''Short Description''': | • '''Short Description''': | ||
A method for decomposing the output prediction of a neural network on a specific input and assigns contribution scores to neurons. | |||
• '''Reference, URL''': https://github.com/kundajelab/deeplift | |||
• ''' | • '''Applicable Business Category''': Research | ||
• ''' | • '''Application in relevant Projects/Initiatives''': N.A. | ||
• ''' | • '''Asset Type''': Library | ||
• ''' | • '''AI Breadth''': Machine Learning | ||
• ''' | • '''Learning Ability''': N.A. | ||
• ''' | • '''Related technologies''': Keras, Tensorflow | ||
• ''' | • '''Applicable Research Area''': Explainable Ai | ||
• ''' | • '''Applicable Technical Category''': Machine learning | ||
• ''' | • '''License Information''': MIT license (MIT) | ||
• '''Audience''': | • '''Related to circularity and sustainability''': No | ||
• '''Audience''': Developers | |||
Latest revision as of 10:31, 27 December 2024
• Short Description: A method for decomposing the output prediction of a neural network on a specific input and assigns contribution scores to neurons.
• Reference, URL: https://github.com/kundajelab/deeplift
• Applicable Business Category: Research
• Application in relevant Projects/Initiatives: N.A.
• Asset Type: Library
• AI Breadth: Machine Learning
• Learning Ability: N.A.
• Related technologies: Keras, Tensorflow
• Applicable Research Area: Explainable Ai
• Applicable Technical Category: Machine learning
• License Information: MIT license (MIT)
• Related to circularity and sustainability: No
• Audience: Developers
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