MLchartDataset catalogue

Overtraining

Term · Chemistry · MLC-T-CHM-008383

A phenomenon in machine learning where a model learns the training data too well, capturing noise and specific patterns that do not generalize to new, unseen data. This results in poor performance on test data, indicating a lack of generalization ability. Techniques like cross-validation and regularization are used to mitigate overtraining.

Table 1. Record
IdentifierMLC-T-CHM-008383
FieldChemistry
SubjectChemistry and Human Health
ReferencesPAC, 2016, 88, 239. 'Glossary of terms used in computational drug design, part II (IUPAC Recommendations 2015)' on page 251 (https://doi.org/10.1515/pac-2012-1204)
Record as JSON 
{
  "id": "MLC-T-CHM-008383",
  "term": "Overtraining",
  "field": "Chemistry",
  "definition": "A phenomenon in machine learning where a model learns the training data too well, capturing noise and specific patterns that do not generalize to new, unseen data. This results in poor performance on test data, indicating a lack of generalization ability. Techniques like cross-validation and regularization are used to mitigate overtraining.",
  "subject": "Chemistry and Human Health",
  "references": [
    "PAC, 2016, 88, 239. 'Glossary of terms used in computational drug design, part II (IUPAC Recommendations 2015)' on page 251 (https://doi.org/10.1515/pac-2012-1204)"
  ],
  "url": "https://mlchart.com/terminology/chemistry/overtraining/"
}

Record 8,908 of 13,676 in Chemistry terminology (MLC-0109). Request the full dataset.