Sökning: "metainlärning"

Hittade 2 uppsatser innehållade ordet metainlärning.

1. 1. Synthetic Meta-Learning: : Learning to learn real-world tasks with synthetic data

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Lukas Lundmark; [2019]
   Nyckelord :;

   Sammanfattning : Meta-learning is an approach to machine learning that teaches models how to learn new tasks with only a handful of examples. However, meta-learning requires a large labeled dataset during its initial meta-learning phase, which restricts what domains meta-learning can be used in. LÄS MER

3. 2. Improving Artist Content Matching with Stacking : A comparison of meta-level learners for stacked generalization

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Fannar Magnússon; [2018]
   Nyckelord :machine learning; stacked generalization; combining classifiers; meta-learning; name disambiguation.; maskininlärning; staplade generaliseringar; kombinerande klassificerare; metainlärning; namn disambiguering.;

   Sammanfattning : Using automatic methods to assign incoming tracks and albums from multiple sources to artists entities in a digital rights management company, where no universal artist identifier is available and artist names can be ambiguous, is a challenging problem. In this work we propose to use stacked generalization to combine the predictions of heterogeneous classifiers for an improved quality of artist content matching on two datasets from a digital rights management company. LÄS MER