total predictions

USAGE SUMMARY

The phrase "total predictions" is correct and usable in written English.
It can be used when referring to the complete number of predictions made in a specific context, such as data analysis or forecasting. Example: "The model generated a total of 150 predictions for the upcoming sales quarter."

✓ Grammatically correct

Science

News & Media

Human-verified examples from authoritative sources

Exact Expressions

21 human-written examples

The success rate was defined as the ratio of correctly predicted GO terms to the total predictions.

BMC Systems Biology

DHFR is the most commonly predicted target, which represents 534 (41%) of the total predictions, followed by plasmepsin 1 (280 predictions – 22%) and plasmepsin 2 (273 predictions – 21 histone deacetylase (184 predictions – 14%) and falcipain 2 (20 predictions – 2%).

Journal of Cheminformatics

We measure the accuracy as number of correct predictions over the number of total predictions.

EPJ Data Science

After 7 such predictions a new user is given a CAPS percentile ranking that takes into account their overall return and accuracy (correct predictions / total predictions).

TechCrunch

As the number of nonignition samples increased, the accuracy of ignition prediction decreased, while the accuracy of nonignition and total predictions increased.

International Journal of Disaster Risk Science

Therefore, we computed PPV, the portion of true positives in the total predictions.

Plosone

Human-verified similar examples from authoritative sources

Similar Expressions

38 human-written examples

SIFT was able to predict deleterious mutations in LacI at approximately 68% total prediction accuracy rate [27], [29].

Plosone

We have also predicted 213 miRNAs of the known homologs from a total prediction of 229 miRNAs in A. thaliana.

BMC Plant Biology

By this way, we could assign a certain percentage of the end time profiles to a test set once and the total prediction error on those time points gave us a measure for the predictive power of the models.

BMC Systems Biology

Parameter uncertainty constitutes only a small part of total prediction uncertainty for the case studies considered here.

Geoderma

For each prediction point, the former can be quantified by a confidence interval, whereas total prediction uncertainty can be represented by constructing a prediction interval.

Engineering Applications of Artificial Intelligence

Expert writing Tips

Best practice

When discussing the accuracy of a model, clearly state the "total predictions" made to provide context for the success rate.

Common error

Avoid implying that "total predictions" refers to the number of correct predictions. "Total predictions" simply means the overall number of predictions, regardless of their accuracy.

Linguistic Context

The phrase "total predictions" functions as a noun phrase, typically used as the object of a preposition or as part of a larger noun phrase. According to Ludwig, it refers to the aggregate count of predictive outcomes in a given scenario.

Expression frequency: Common

Frequent in

Science

70%

News & Media

15%

Formal & Business

10%

Less common in

Encyclopedias

1%

Wiki

2%

Reference

2%

Ludwig's WRAP-UP

In summary, "total predictions" is a common noun phrase that refers to the overall count of predictions made in a given context. Ludwig AI confirms that it is grammatically sound and suitable for use in various writing styles. While its meaning is straightforward, it's important to avoid confusion with the accuracy of those predictions. Alternatives such as "overall forecasts" or "aggregate predictions" can be used to add variety to your writing. Remembering best practices, such as providing the "total predictions" when discussing a model's performance, ensures clarity in communication.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

overall forecasts

This alternative emphasizes the comprehensive nature of the forecasts, similar to "total predictions".

aggregate predictions

This alternative highlights the combined nature of the predictions, much like "total predictions".

complete projections

This alternative focuses on the entirety of the projections, mirroring the meaning of "total predictions".

cumulative forecasts

This alternative stresses the accumulated sum of the forecasts, akin to "total predictions".

combined predictions

This focuses on predictions that have been added together or are coming from the same source, maintaining a similar nuance to "total predictions".

sum of predictions

This is more direct, explicitly stating that predictions have been added together.

total anticipated outcomes

This uses a broader vocabulary, replacing "predictions" with "anticipated outcomes" but conveying the same overall meaning as "total predictions".

all predictions

This is a more concise phrasing which still captures the inclusivity of "total predictions".

entire set of predictions

This emphasizes that all predictions are considered as part of a complete collection, similar to the meaning of "total predictions".

full count of predictions

This alternative highlights a numerical representation of the predictions made.

FAQs

How is accuracy calculated based on "total predictions"?

Accuracy is typically calculated as the number of correct predictions divided by the "total predictions". This ratio provides a measure of the model's performance.

What does "total predictions" mean in the context of machine learning?

In machine learning, "total predictions" refers to the complete set of predictions generated by a model, encompassing both correct and incorrect outcomes.

What can I use instead of "total predictions"?

You can use alternatives like "overall forecasts", "aggregate predictions", or "complete projections" depending on the context.

Why is it important to know the "total predictions" when evaluating a model?

Knowing the "total predictions" is crucial for understanding the context of other metrics like precision and recall. It provides a baseline for assessing the model's performance relative to the overall number of attempts.