concept
active
concept:feature-engineering

Feature engineering

Domain of techniques for constructing informative features from raw data; covariance pooling is a feature engineering method for token sequences.

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Papers (1)

paper

Related by similarity (8)

cosine ≥ 0.65 · no typed edge

Entities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.

  • Metaphor treating each system feature or function as a separate application that can be independently loaded and managed.
  • Method of optimizing input to cause a neuron to fire maximally, used to characterize what a neuron detects; establishes causal link
  • Scalar function of the input corresponding to a direction in the vector space of neuron activations; claimed to be the fundamental unit of neural networks
  • Research thread within About Blank concerning the structure and relational properties of neural network feature representations; covariance pooling tangentially supports this thread.
  • A class of methods that modify how models internally process representations; SOO fine-tuning fits within this framework
  • Action Featuresconcept0.760
    Dual interpretation of features: in addition to responding to inputs, features also act to increase probability of specific output tokens
  • Domain Engineeringframework0.760
    Approach to building reusable domain models.
  • Feature splittingconcept0.756
    Phenomenon where a feature in a small SAE splits into multiple finer features in a larger SAE.