test data

USAGE SUMMARY

"test data" is correct and usable in written English.
You can use it when referring to data that is collected and used to evaluate the performance of a system, model, or product. For example, "The scientists used test data to evaluate the effectiveness of the new vaccine."

✓ Grammatically correct

Science

News & Media

Academia

Human-verified examples from authoritative sources

Exact Expressions

60 human-written examples

Test data generation with PADS.

Princeton University

Are D.C. school officials hiding test data?

The Washington Post

Drug companies want protection for their test data.

The New York Times

Russia has not given him the test data, he said.

The New York Times

But we evaluated our new test data.

Massachusetts Institute of Technology

These are determined from existing test data.

Applied Thermal Engineering

Preliminary test data will also be presented.

Surface and Coatings Technology

Results were verified using experimental test data.

8th International Conference on Compressors and their Systems

Here are the examples using EDGE test data set.

Cornell University

See the test data file for examples of this format.

Cornell University

The directory /programs/LDAK/examples contains test data and results.

Cornell University

Expert writing Tips

Best practice

Ensure your "test data" is representative of the population or scenario you're trying to model to avoid biased results.

Common error

Avoid assuming correlation implies causation when analyzing "test data". Always consider potential confounding variables and conduct further analysis to establish causality.

Linguistic Context

The phrase "test data" primarily functions as a noun phrase, acting as a subject or object within a sentence. Ludwig AI confirms its correct usage, supported by numerous examples demonstrating its role in various contexts.

Expression frequency: Very common

Frequent in

Science

42%

News & Media

35%

Academia

23%

Less common in

Formal & Business

0%

Encyclopedias

0%

Wiki

0%

Ludwig's WRAP-UP

In summary, "test data" is a grammatically correct and very common noun phrase, used to refer to data specifically used for testing and validation purposes. Ludwig AI confirms this, citing numerous examples across diverse fields like science, news, and academia. It is crucial to understand the context and source of "test data" to ensure its proper interpretation and application. While the phrase itself maintains a neutral register, its usage is more prevalent in formal and scientific settings. Related phrases include "validation data", "experimental results", and "sample data", each offering slightly different nuances. When writing about "test data", be clear about its source and collection methodology, and avoid misinterpreting correlations as causations.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

validation data

Emphasizes the use of data for confirming the accuracy or reliability of something.

evaluation data

Highlights data specifically gathered for the purpose of evaluating performance or quality.

experimental results

Focuses on the outcome of tests, specifically the results obtained.

trial data

Focuses on data collected during a trial or experiment.

sample data

Highlights that the data is a representative subset used for testing.

benchmark data

Indicates that the data serves as a standard for comparison.

empirical data

Emphasizes that the data is based on observation or experience.

assessment data

Stresses the use of data for evaluation and judgment.

training data

Points to data used to train a model or system before testing.

verification results

Highlights the results obtained during a verification process.

FAQs

How is "test data" used in software development?

"Test data" is crucial for verifying software functionality, performance, and reliability. It helps identify bugs, ensures code quality, and validates that the software meets specified requirements.

What's the difference between "training data" and "test data" in machine learning?

"Training data" is used to train a machine learning model, while "test data" evaluates its performance on unseen data, assessing its ability to generalize.

How can I generate effective "test data"?

Effective "test data" should cover a wide range of scenarios, including normal, boundary, and edge cases. Tools like data generators and manual creation can be used to ensure comprehensive coverage.

Why is it important to anonymize "test data"?

Anonymizing "test data" protects sensitive information and complies with data privacy regulations. Techniques like masking, substitution, and pseudonymization can be used to de-identify data while preserving its utility for testing purposes.