mean fold error

USAGE SUMMARY

The phrase "mean fold error" is correct and usable in written English.
You can use it when describing the results of calculating the average of the difference between the predicted value and the true value of a dataset. For example: "The mean fold error of our calculations was 0.15."

✓ Grammatically correct

Science

Human-verified examples from authoritative sources

Exact Expressions

3 human-written examples

The mean fold error of our selected model (approach (c)) was 2.29.

Journal of Cheminformatics

For each of these 5 modified Vss-target datasets, we ran again the Bagging M5P regression algorithm and measured its geometric mean fold error (GMFE), averaging the results over the 5 runs.

Journal of Cheminformatics

This is a reasonable accuracy when considering the mean fold error reported in the literature for the interspecies scaling of 1.56 – 2.78 [52] and an animal to human extrapolation of Vss for a small range of drugs showing an average error of 1.82 [21.82

Journal of Cheminformatics

Human-verified similar examples from authoritative sources

Similar Expressions

57 human-written examples

The Geometric Mean Fold Errors (GMFEs) shown in that table were calculated as: GMFE = antilog10 (MAE) [3].

Journal of Cheminformatics

For estimating PK measures such as AUC, Cmax, tmax, and ke, a variety of metrics including absolute average fold error (AAFE), root mean squared error (RMSE), mean ratio obs/pred), and proportion of estimates falling within a specified fold-error (i.e. 2-fold, 3-fold etc)., have been utilized.

CPT: Pharmacometrics and Systems Pharmacology

To estimate the error of the predicted protein concentrations, bootstrapping and Monte Carlo cross-validation are performed, with minimization of the mean-fold error (MFE) as objective function.

Bioinformatics

Expression values are mean relative expression or mean fold induction ± standard error of the mean (SEM).

Plosone

Values are expressed as the mean fold induction ± standard error.

Breast Cancer Research

The measurements are presented as mean fold changes ± standard error of the mean (SEM).

BMC Cancer

Mean fold differences and standard errors were calculated.

BMC Genomics

Experiments were repeated eight times and for each marker a mean fold change in expression and standard error was calculated.

DMM Disease Models and Mechanisms

Expert writing Tips

Best practice

When reporting the "mean fold error", always specify the context, such as the model or dataset used, for clarity and reproducibility.

Common error

Avoid using "mean fold error" interchangeably with metrics like RMSE (root mean squared error) or MAE (mean absolute error). Each metric provides different insights into model performance; choosing the right one depends on the specific goals of your analysis.

Linguistic Context

The phrase "mean fold error" functions as a noun phrase that represents a statistical metric used to quantify the average magnitude of error in predictions, specifically focusing on the fold difference between predicted and actual values. As Ludwig AI confirms, it's accurate for describing such results.

Expression frequency: Rare

Frequent in

Science

100%

Less common in

News & Media

0%

Formal & Business

0%

Academia

0%

Ludwig's WRAP-UP

In summary, "mean fold error" is a noun phrase denoting a specific statistical metric used to evaluate predictive accuracy, particularly in scientific domains. According to Ludwig AI, the phrase is grammatically sound and suitable for use. It quantifies the average fold difference between predicted and observed values, providing a measure of model performance. While not exceptionally common, its usage is consistent within scientific literature, where it serves to report and compare the accuracy of models, as validated by Ludwig.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

average fold error

Replaces "mean" with "average", a direct synonym, preserving the statistical context.

geometric mean fold error

Specifies the type of mean being used, adding precision.

mean absolute fold error

Clarifies that absolute values are used before calculating the mean, affecting the result.

average percentage fold error

Expresses the error as a percentage of the fold change, providing a relative measure.

mean error in fold change

Rephrases the original to emphasize error within the fold change calculation.

typical fold error

Employs "typical" as a less formal synonym for "mean", suitable for broader contexts.

representative fold error

Indicates a fold error value that is characteristic of the data set.

fold error average

Inverts the word order without sacrificing meaning, primarily stylistic.

aggregate fold error

Substitutes "mean" with "aggregate", highlighting the combined nature of the error.

central tendency of fold errors

Describes the "mean fold error" conceptually, focusing on central tendency.

FAQs

How is "mean fold error" calculated?

The "mean fold error" is calculated by averaging the fold errors between predicted and observed values. The fold error for a single data point is often computed as max(predicted/observed, observed/predicted) to ensure a value greater than or equal to 1.

What does a high "mean fold error" indicate?

A high "mean fold error" indicates that, on average, the predictions deviate substantially from the observed values. This suggests a lower accuracy of the model or method being evaluated.

Is there an alternative to using the "mean fold error"?

Yes, alternatives include the "average fold error", "mean absolute error" (MAE), and root mean squared error (RMSE). The choice depends on the specific requirements of the analysis.

In what contexts is "mean fold error" commonly used?

The "mean fold error" is commonly used in scientific contexts, particularly in fields like cheminformatics and systems pharmacology, for assessing the accuracy of predictive models. It measures how well predictions match observed experimental values.