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Generating Explainable and Effective Data Descriptors Using Relational Learning: Application to Cancer Biology
[chapter]
2020
Lecture Notes in Computer Science
The key to success in machine learning is the use of effective data representations. The success of deep neural networks (DNNs) is based on their ability to utilize multiple neural network layers, and big data, to learn how to convert simple input representations into richer internal representations that are effective for learning. However, these internal representations are sub-symbolic and difficult to explain. In many scientific problems explainable models are required, and the input data is
doi:10.1007/978-3-030-61527-7_25
fatcat:57l4nemeqrdbrc6av7fl2pdlxq