sparse data

USAGE SUMMARY

The term "sparse data" is correct and usable in written English.
You can use it to describe data that contains very few items or records. For example, "This patient's medical information contained sparse data, so we were unable to accurately diagnose the condition."

✓ Grammatically correct

Science

Academia

News & Media

Human-verified examples from authoritative sources

Exact Expressions

60 human-written examples

Learning from missing and sparse data.

Princeton University

can apply standardization to sparse data efficiently.

Stanford University

Probability distribution estimation from sparse data.

Cornell University

Most response surface experiments involve sparse data.

Journal of Statistical Planning and Inference

Interpolated estimation of Markov source parameters from sparse data.

Cornell University

So of course, this is very sparse data.

Massachusetts Institute of Technology

In the world of re-identifying, they talk about "sparse data" approaches to de-anonymisation.

The Guardian - Tech

Subbiah M, Srinivasan MR. Classification of 2 × 2 sparse data sets with zero cells.

Nature

"We are talking about triangulating on very sparse data," Mr. Gruzen said.

The New York Times - Tech

However, the weighted sums approach should not be used when analyzing sparse data.

Columbia University

Such algorithms encounter problems with sparse data or patterns that are widely dispersed across the text.

Cornell University

Expert writing Tips

Best practice

When describing data limitations in research or analysis, use "sparse data" to accurately convey the concept of having a limited number of data points. This term is especially relevant in statistical modeling, machine learning, and scientific studies where data density affects the robustness of results.

Common error

Avoid using "sparse data" interchangeably with "missing data". "Sparse data" refers to datasets where many values are zero or undefined, especially when the potential data space is large. "Missing data", on the other hand, refers to individual data points absent from a dataset, regardless of the overall data density. Understanding this distinction ensures accurate communication of data characteristics.

Linguistic Context

The phrase "sparse data" functions as a noun phrase, where "sparse" is an adjective modifying the noun "data". Ludwig AI confirms its grammatical correctness. It is commonly used to describe datasets where the majority of values are zero or missing.

Expression frequency: Very common

Frequent in

Science

54%

Academia

30%

News & Media

11%

Less common in

Formal & Business

5%

Encyclopedias

0%

Wiki

0%

Ludwig's WRAP-UP

In summary, the phrase "sparse data" is grammatically correct and frequently used, particularly in scientific and academic contexts, to describe datasets with limited information. Ludwig AI confirms this. While alternatives like "limited data" or "scarce data" exist, "sparse data" is precise in denoting a situation where available data points are few relative to the potential data space. When working with such data, it's crucial to employ appropriate analytical techniques and to clearly communicate the limitations imposed by data sparsity.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

limited data

Focuses on the restricted amount of data available.

scarce data

Emphasizes the rarity and limited availability of the data.

insufficient data

Highlights that the data is not enough for a particular purpose.

fragmentary data

Suggests that the available data is incomplete and broken into pieces.

incomplete data

Highlights that the data is missing some elements.

patchy data

Indicates that the data is only available in certain areas or time periods.

thin data

Describes the data as being weakly spread or insubstantial.

meager data

Emphasizes the poor quality and insufficient quantity of the data.

scant data

Similar to 'scarce', this emphasizes a minimal quantity of data.

rare data

Underlines the infrequency of data occurrence.

FAQs

How can I use "sparse data" in a sentence?

You can use "sparse data" to describe situations where the available data is limited or incomplete. For example, "The model's accuracy was affected by the "sparse data" available for training".

What are some alternatives to saying "sparse data"?

Alternatives include "limited data", "scarce data", or "insufficient data" depending on the nuance you want to convey.

When is it appropriate to use the term "sparse data"?

Use "sparse data" when you need to highlight that the amount of available data is very small relative to the total possible data. This is common in fields like statistics, machine learning, and signal processing where data density can impact the reliability of results.

What techniques are used to deal with "sparse data" in machine learning?

Common techniques include regularization, imputation, and using algorithms specifically designed for "sparse data" like sparse matrix factorization or certain types of neural networks. These methods aim to improve model performance despite the data limitations.