a large dataset

USAGE SUMMARY

The phrase "a large dataset" is correct and usable in written English.
It can be used when referring to a collection of data that is substantial in size, often in the context of data analysis, research, or machine learning. Example: "To improve the accuracy of our model, we need to train it on a large dataset that includes diverse examples."

✓ Grammatically correct

Science

News & Media

Formal & Business

Human-verified examples from authoritative sources

Exact Expressions

60 human-written examples

The researchers then used that information to look at a large dataset of genetic information from about 900 dogs representing 80breedss.

The New York Times - Science

However, results on a large dataset are not reported.

EURASIP Journal on Audio, Speech, and Music Processing

Handling such a large dataset was not an easy task.

Journal of Internet Services and Applications

As aforementioned, 100Credit has a large dataset from multiple sources.

Financial Innovation

To use ML and AI effectively, you often need to have a large dataset.

TechCrunch

Having a large dataset will help to overcome any noise we expect".

TechCrunch

And labelling a large dataset takes hundreds of thousands of dollars and months of time.

TechCrunch

Patent-paper pairs are detected using text-mining algorithms applied on a large dataset.

Research Policy

The study was conducted on a large dataset of 73 catchments within the eastern US.

Journal of Hydrology

Other times, when given a large dataset of face images, they'll learn models that only a computer can understand.

TechCrunch

Analysis were conducted on a large dataset (more than 1400 sampled sites, mainly on rural environments).

Acta Oecologica

Expert writing Tips

Best practice

When using "a large dataset" in scientific writing, specify the size or characteristics of the dataset to provide context and credibility.

Common error

Avoid using "a large dataset" without providing any context about its composition, source, or relevant attributes. This can make your analysis seem vague and less impactful.

Linguistic Context

The phrase "a large dataset" functions as a noun phrase, where 'large' is an adjective modifying the noun 'dataset'. Ludwig provides examples illustrating its use in various contexts, affirming its grammatical correctness.

Expression frequency: Very common

Frequent in

Science

68%

News & Media

21%

Formal & Business

11%

Less common in

Wiki

0%

Encyclopedias

0%

Social Media

0%

Ludwig's WRAP-UP

In summary, the phrase "a large dataset" is a common and grammatically correct term used to describe a substantial collection of data. As Ludwig AI confirms, it is frequently employed in scientific, news, and formal business contexts. When using this phrase, it's beneficial to provide specifics about the dataset's characteristics to enhance clarity. Common errors include vagueness, which can be avoided by specifying dataset attributes. Alternatives include "extensive data collection" and "substantial data resource". The phrase functions as a noun phrase, serves the purpose of describing a data collection, and typically appears in formal and scientific registers.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

vast collection of data

Emphasizes the size of the data using 'vast' instead of 'large'.

extensive database

Replaces 'dataset' with 'database', focusing on the structured nature of the data.

significant volume of data

Focuses on the size using 'volume' and the importance using 'significant'.

massive data pool

Uses 'massive' to highlight the size and 'pool' to suggest a shared resource.

considerable amount of data

Emphasizes the quantity of data using 'considerable amount'.

substantial data resource

Highlights the value and amount of the data available for use.

extensive data collection

Focuses on the collection process and emphasizes the comprehensiveness of the gathered data.

comprehensive data repository

Emphasizes the organized and complete nature of the stored data.

detailed data archive

Emphasizes the level of detail and the archival nature of the data.

broad range of data

Highlights the variety and scope of the data included.

FAQs

How can I effectively use "a large dataset" in data analysis?

Start by cleaning and preprocessing the data to handle missing values and outliers. Then, explore the data to identify patterns and relationships, and use appropriate statistical methods to draw meaningful conclusions.

What are some alternatives to saying "a large dataset"?

You can use alternatives like "extensive data collection", "substantial data resource", or "vast collection of data" to add variety to your writing.

Why is using "a large dataset" important in machine learning?

A larger dataset typically allows machine learning models to learn more complex patterns and generalize better to unseen data, leading to improved accuracy and reliability.

What are the challenges of working with "a large dataset"?

Challenges include increased computational requirements, longer processing times, and the need for efficient data storage and management solutions. Techniques like data sampling and distributed computing can help mitigate these issues.