HOLDOUT DATA Meaning and
Definition
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Holdout data is a term used in statistical analysis and machine learning to refer to a subset of data that is intentionally withheld from the modeling or training process. It is a representative sample of the overall dataset that is kept separate, serving as an independent set for testing and evaluating the performance of a predictive model. Holdout data is typically not used for model fitting, feature selection, or hyperparameter tuning to avoid data leakage and overfitting.
This reserved portion of data is preserved until the very end of the analysis, where it serves as a benchmark for assessing the predictive accuracy and generalization ability of the trained model. By withholding a portion of the data, holdout data simulates a real-world scenario where the model is deployed on unseen new data to estimate its performance in a production environment.
The purpose of holdout data is to evaluate the performance of a model on unseen data and to estimate its ability to generalize beyond the training set. It helps to determine whether the model has learned the underlying patterns in the data and can make accurate predictions on new, unseen instances. The evaluation metrics calculated on the holdout data provide an unbiased estimate of the model’s performance and help guide decisions regarding its deployment.
In summary, holdout data is a subset of data that is not used for training a predictive model but kept separately to assess the model’s performance on unseen data. It serves as a measure of the model's ability to generalize and make accurate predictions in real-world scenarios.
Common Misspellings for HOLDOUT DATA
- goldout data
- boldout data
- noldout data
- joldout data
- uoldout data
- yoldout data
- hildout data
- hkldout data
- hlldout data
- hpldout data
- h0ldout data
- h9ldout data
- hokdout data
- hopdout data
- hoodout data
- holsout data
- holxout data
- holcout data
- holfout data
- holrout data
Etymology of HOLDOUT DATA
The term "holdout data" is a compound word, with each part having its own etymology:
1. Holdout: The word "holdout" comes from the verb "hold out", which means to resist or refuse to give in. It originated in the late 16th century, combining "hold" and "out". The term was originally used to describe people who refused to comply with certain agreements or demands.
2. Data: The word "data" is the plural form of the Latin word "datum", which means "something given" or "a fact". In modern usage, "data" refers to information or facts that are collected, analyzed, and used for various purposes.
When combined, "holdout data" refers to a subset of data that is withheld, kept separate, or not used within a particular context, typically in statistical analysis or machine learning.
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