Underfitting is a condition in supervised machine learning where a model lacks sufficient capacity to capture the underlying pattern in the training data, producing high error on both training and held-out sets. The parameters are: (1) a trained model with fixed architecture and hyperparameters, (2) a learning procedure that has exhausted its iterations or resources, (3) performance metrics (e.g., MSE, accuracy) that remain unacceptably high on both training and validation data. Persistence mechanism: the concept endures through statistical learning theory, textbooks, and engineering practice — it is named, taught, and invoked as a diagnostic category whenever models fail to converge toward adequate fit. [formal: underfitting | substrate: behavior | horizon: hours | explicit: yes | epoch: 0.01]
Accepted ontology entry
underfitting
Underfitting is a condition in supervised machine learning where a model lacks sufficient capacity to capture the underlying pattern in the training data, producing high error on both training and held-out sets. The parameters are: (1) a t…
Definition
Why it is in scope
A condition in machine learning where a model lacks sufficient capacity to capture the underlying pattern in training data, producing high error on both training and test sets. Built to persist through diagnostic plots (learning curves) and hyperparameter tuning protocols.
Names and aliases
- underfittingen · CANONICAL
Relations from this entry
- cmruf04x1013cr671g8zou4lnINSTANCE_OF →
Underfitting is a specific kind of error in machine learning: a model that is too simple to capture the structure in data. Remove the concept of error and underfitting ceases to operate as a diagnostic category.
- cmrxj3acr03cmsoacx73fal1oDEPENDS_ON →
Underfitting is a diagnostic concept in statistical and machine learning modeling: the condition where a model is too simple to capture patterns in data. Remove statistics and underfitting has no framework to operate — it cannot be defined, measured, or diagnosed. The removal test passes.
- cmsa8waf503477skqyquk9janDERIVED_FROM →
Chronological and conceptual priority (Law 7): the concept of training models predates and fed into the identification of underfitting as a distinct failure mode. Underfitting only makes sense as a concept within the broader practice of training.
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No accepted relations in this direction.
Record identity
- Created
- Aug 9, 2026, 3:03 PM UTC
- Content hash
- 0292d6b863b6887687fe3b7833b9599389157ab7770fb2863109c64400ef2431