arbitrary data

USAGE SUMMARY

The phrase "arbitrary data" is correct and usable in written English.
It can be used in contexts where data is chosen or assigned without any specific reason or pattern, often in discussions about data analysis or programming. Example: "In our experiment, we used arbitrary data to test the algorithm's performance under various conditions."

✓ Grammatically correct

Science

Academia

News & Media

Human-verified examples from authoritative sources

Exact Expressions

60 human-written examples

arbitrary data.

Artificial Intelligence

Minimization means to maximize the sharing in arbitrary data structures.

Electronic Notes in Theoretical Computer Science

Nintendo chose arbitrary programming instructions and arranged them in a unique sequence to create a purely arbitrary data stream.

Harvard University

It can be brought to a satisfactory conclusion and convincingly verified using arbitrary data.

The Air Engine Stirling Cycle Power for a Sustainable Future

With an effective script, a hacker can insert arbitrary data into the cache of one of these servers in about 10 seconds.

MIT Technology Review

The MGRNN provides two additional features: (1) it is trainable with arbitrary data as long as a suitable metric exists.

Neural Networks

In this paper we describe an efficient, non-blocking mechanism for reordering, which can be used over arbitrary data streams from files, indexes, and continuous data feeds.

University of California, Berkeley

With various colleagues I have developed tools ranging from simple but optimal histograms to time and frequency domain analysis for arbitrary data modes and time sampling.

Harvard University

We discuss the issues and compromises involved implementing equation solvers with fields comprising arbitrary data types on GPUs and other current compute devices.

Procedia Computer Science

Newer protocols (such as http) or old protocols designed to handle arbitrary data (such as FTP) are actually going to be more likely to get your data transferred all in one piece.

Columbia University

We have implemented a number of approaches for improving this situation such as devising a simple but versatile scripting language for data acquisition, a means of handling arbitrary data formats, and a new modular architecture for luminescence instrumentation.

Radiation Measurements

Expert writing Tips

Best practice

When using "arbitrary data" for testing, document the range and distribution of values to ensure reproducibility and to avoid unintentionally skewing results.

Common error

Avoid using "arbitrary data" interchangeably with "random data" without considering the context. "Arbitrary data" implies a choice made without a specific pattern, while "random data" specifically refers to data generated by a random process. Ensure your terminology accurately reflects the data's origin and characteristics.

Linguistic Context

The phrase "arbitrary data" functions as a noun phrase where "arbitrary" acts as an adjective modifying the noun "data". It describes data that is chosen without a specific reason or pattern. As Ludwig AI states, this phrase is correct and usable in written English.

Expression frequency: Very common

Frequent in

Science

59%

Academia

22%

News & Media

8%

Less common in

Formal & Business

6%

Encyclopedias

0%

Wiki

0%

Ludwig's WRAP-UP

In summary, "arbitrary data" is a grammatically sound and frequently employed phrase. Ludwig AI confirms its usability, and it generally functions as a noun phrase describing data selected without a specific pattern or constraint. It is most often used in scientific and academic contexts, with its purpose being to signify that the data's specific values aren't critical, making it suitable for demonstrations, testing, or placeholders. While primarily formal, understanding its role and using it accurately will enhance clarity in technical and academic communication.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

random data

Replaces 'arbitrary' with 'random', suggesting a lack of pattern or predictability in the data.

unstructured data

Focuses on the lack of a predefined structure or format in the data.

undefined data

Highlights the lack of clear definition or specification for the data.

unspecified data

Similar to 'undefined data', emphasizing the absence of explicit specification.

variable data

Emphasizes that the data can change or vary without a set pattern.

generic data

Suggests that the data is not tailored to a specific purpose or context.

artificial data

Implies data created for testing purposes, potentially lacking real-world relevance.

synthetic data

Similar to 'artificial data', referring to data generated rather than observed.

sample data

Refers to a subset of data used for analysis or testing, potentially chosen arbitrarily.

test data

Data specifically used for testing a system or algorithm.

FAQs

How is "arbitrary data" used in programming?

"Arbitrary data" is often used in programming examples or testing scenarios where the specific data values are not critical, but the code needs to handle various inputs. It helps ensure the program is robust and can manage different data types and ranges without crashing or producing incorrect results.

What's the difference between "arbitrary data" and "random data"?

"Arbitrary data" refers to data selected without a specific method or constraint, while "random data" is generated using a random process to ensure each value has an equal chance of being selected. The distinction lies in the data's generation method and the presence or absence of intentional selection.

Can I use "arbitrary data" in formal scientific writing?

Yes, "arbitrary data" is acceptable in formal scientific writing, especially when describing methods or simulations. However, ensure clarity by specifying the characteristics of the data used (e.g., range, distribution) to maintain scientific rigor and reproducibility.

What are some examples of when to use "arbitrary data"?

"Arbitrary data" is appropriate when demonstrating a concept, testing software, or creating placeholder content. For instance, you might use "arbitrary data" to populate a database during development or to illustrate a data visualization technique without relying on specific real-world datasets.