training residuals vs validation residuals

Both 'training residuals' and 'validation residuals' are correct and commonly used terms in the context of statistical modeling. 'Training residuals' refer to the differences between the observed and predicted values in the training dataset, while 'validation residuals' refer to the differences in the validation dataset. The choice between the two depends on the specific phase of the modeling process being referred to.

Last updated: March 17, 2024 • 653 views

training residuals

This phrase is correct and commonly used in statistical modeling.

This term refers to the differences between the observed values and the values predicted by a model using the training dataset. It is used to assess the model's performance during the training phase.

Examples:

The analyst examined the training residuals to evaluate the model's fit to the data.

Show examples from the web [+]

... for the effective design of a sports conditioning program to sequence related fitness components taking into account of the relevant specific training residuals.
Therefore, an effective sequencing of different training targets should take into account the duration of different training residuals. Table 1. Training residuals of ...
The coaches' knowledge about training residuals and temporal detraining is extremely important for planning transition at some stage of athletes' preparation ...
The rate of loss of training effects and respective training residuals vary widely for ... be well though based on delayed training effects and training residuals, ...

Alternatives:

residuals from the training set
model residuals from training data
training error residuals
training set residuals
residuals in the training phase

validation residuals

This phrase is correct and commonly used in statistical modeling.

This term refers to the differences between the observed values and the values predicted by a model using the validation dataset. It is used to assess the model's performance on unseen data.

Examples:

The researcher analyzed the validation residuals to determine the model's generalization ability.

Show examples from the web [+]

I. Derivation of Expected Values of Cross-Validation Residuals. Used in Macromolecular Least-Squares Refinement. IAN J. TICKLE, ROMAN A. LASKOWSKI ...
(1993), have examined the role of leave-one-out cross-validation residuals for model fitting and diagnostics. In Section 2 we discuss some of the relevant theory .
Figure 5: Cross-validation residuals obtained by kriging residual (ROKFD) (gray curves). Dark line is the mean of cross-validation residuals and dashed line is ...
variance based on validation residuals (dashed line) and based on training residuals. (dash-dotted line). (c) Width of standard error bars for the more advanced ...

Alternatives:

residuals from the validation set
model residuals from validation data
validation error residuals
validation set residuals
residuals in the validation phase

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training residuals vs validation residuals