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- Author: Pavel Brazdil
- Publisher: Springer
- ISBN-10: 3030670260
- ISBN-13: 9783030670269
- Format: 15.6 x 23.4 x 1.9 cm, minkšti viršeliai
- Language: English
- SAVE -10% with code: EXTRA
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Description
Introduction.- Part I, Basic Architecture of Metalearning and AutoML Systems.- Metalearning Approaches for Algorithm Selection I.- Evaluating Recommendations of Metalearning / AutoML Systems.- Metalearning Approaches for Algorithm Selection II.- Automating Machine Learning (AutoML) and Algorithm Configuration.- Dataset Characteristics (Metafeatures).- Automating the Workflow / Pipeline Design.- Part II, Extending the Architecture of Metalearning and AutoML Systems.- Setting Up Configuration Spaces and Experiments.- Using Metalearning in the Construction of Ensembles.- Algorithm Recommendation for Data Streams.- Transfer of Metamodels Across Tasks.- Automating Data Science.- Automating the Design of Complex Systems.- Repositories of Experimental Results (OpenML).- Learning from Metadata in Repositories.
EXTRA 10 % discount with code: EXTRA
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- Author: Pavel Brazdil
- Publisher: Springer
- ISBN-10: 3030670260
- ISBN-13: 9783030670269
- Format: 15.6 x 23.4 x 1.9 cm, minkšti viršeliai
- Language: English English
Introduction.- Part I, Basic Architecture of Metalearning and AutoML Systems.- Metalearning Approaches for Algorithm Selection I.- Evaluating Recommendations of Metalearning / AutoML Systems.- Metalearning Approaches for Algorithm Selection II.- Automating Machine Learning (AutoML) and Algorithm Configuration.- Dataset Characteristics (Metafeatures).- Automating the Workflow / Pipeline Design.- Part II, Extending the Architecture of Metalearning and AutoML Systems.- Setting Up Configuration Spaces and Experiments.- Using Metalearning in the Construction of Ensembles.- Algorithm Recommendation for Data Streams.- Transfer of Metamodels Across Tasks.- Automating Data Science.- Automating the Design of Complex Systems.- Repositories of Experimental Results (OpenML).- Learning from Metadata in Repositories.
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