A few useful things to know about machine learning

Domingos, P. (2012). A few useful things to know about machine learning. Communications of the ACM, 55(10), 78-87.

Type

Journal article

Intellectual base

Primary research

Year

2012

Link

https://doi.org/10.1145/2347736.2347755matched

Cited from

statistics_experimental_design

Cited by

1 citation across 1 artifact.

Primes

• Overfitting
  • A claim like "the model works" resolves into "the model was trained on sample S from distribution D; evaluated on S, performance is P1; evaluated on held-out sample from D (or on deployment data), performance is P2; the gap P1 − P2 is [negligible / moderate / large]; where the gap is large, the model has captured training-specific patterns [noise, rare cases, sampling artifacts] that don't transfer; the remedy is [more data, regularization, simpler hypothesis class, feature selection, validation-based early stopping] chosen for the specific overfitting mechanism

Verification

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