dice coefficient

USAGE SUMMARY

'dice coefficient' is a correct and usable phrase in written English.
You can use it to refer to a particular statistical measure of inter-rater agreement, also known as the Sørensen–Dice coefficient. For example, you might say, "We used the Dice coefficient to measure the level of agreement between two sets of survey responses."

✓ Grammatically correct

Science

Human-verified examples from authoritative sources

Exact Expressions

60 human-written examples

The dice coefficient was on average 0.89 and 0.94 respectively.

EJNMMI Research

The quantitative comparison is made by the dice coefficient.

EURASIP Journal on Advances in Signal Processing

In order to measure segmentation success, the Dice coefficient was obtained as 89.3%.

Measurement

A mean accuracy of Dice coefficient obtained is 0.67 in total.

NeuroImage: Clinical

Table 3 shows the results of measuring the similarity of two morphosyllables with the Dice coefficient and the improved Dice coefficient methods.

Computational Social Networks

Performance was measured using the Jaccard index (J) and Dice coefficient.

Journal of Neuroscience Methods

Besides an Overlapping and Dice Coefficient, SubVIS includes the Jaccard Index as a similarity measure.

Brain Informatics

We compare the similarity of each pair of morphosyllables according to the improved Dice coefficient.

Computational Social Networks

So, using the improvement of the Dice coefficient, we have fDice("nguyen," "nguyn") = 0.727.

Computational Social Networks

A Dice coefficient was then calculated on the results of this alignment.

Journal of Cheminformatics

Dice coefficient [24] also called Sorensen, Czekannowski Hodgkin-Richards [25] or Morisita [26].

Journal of Big Data

Expert writing Tips

Best practice

When reporting the "dice coefficient", always specify the data and method used to derive the coefficient to ensure reproducibility and proper interpretation.

Common error

Avoid assuming a high "dice coefficient" automatically implies practical significance. A high coefficient indicates strong overlap, but the context and magnitude of the data should also be considered.

Linguistic Context

The phrase "dice coefficient" functions as a noun phrase, specifically a technical term, often used within scientific and statistical contexts. It is a quantifiable measure. As Ludwig confirms, it is a correct and usable phrase.

Expression frequency: Very common

Frequent in

Science

100%

Less common in

News & Media

0%

Formal & Business

0%

Academia

0%

Ludwig's WRAP-UP

The term "dice coefficient" is a statistically sound and commonly used metric, as confirmed by Ludwig. It serves as a noun phrase, primarily within the scientific domain, to quantify the similarity between datasets. As a formal term, it's best suited for technical contexts, demanding precise and reproducible language. The examples from Ludwig underscore its frequent use in scientific publications, highlighting its role in ensuring objective assessments across various analytical studies. A high coefficient indicates a strong overlap, but practical significance should always be carefully considered alongside the context and magnitude of the data.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

sorensen-dice index

This alternative uses the full name of the metric, specifying the scientists credited with its development, for a more formal tone.

sorensen index

This alternative shortens the metric name, referring only to Sorensen, maintaining a formal tone.

similarity index

This term broadens the concept, referring to a general measure of similarity, applicable beyond specific methods.

similarity coefficient

This is a general term for any coefficient measuring similarity. It's broader than the specific "dice coefficient".

overlap index

Focuses on the degree of overlap between two sets or samples, a key aspect measured by the dice coefficient.

association measure

Highlights the statistical association between variables, similar to the dice coefficient's function.

resemblance coefficient

Emphasizes the degree of resemblance or similarity, offering a less technical alternative.

tversky index

This is a generalization of the Dice coefficient and the Tanimoto coefficient. It measures the overlap between two sets.

jaccard index

While related, the Jaccard index calculates similarity differently, focusing on the ratio of shared features to total features.

czekannowski index

This alternative provides a synonym for the Dice coefficient, using another name associated with the same metric.

FAQs

How is the "dice coefficient" calculated?

The "dice coefficient" is calculated as 2 times the number of common elements divided by the sum of the number of elements in each set. The formula is: 2|X ∩ Y| / (|X| + |Y|).

What does a high "dice coefficient" indicate?

A high "dice coefficient", close to 1, indicates a high degree of similarity and overlap between two sets. This often suggests strong agreement or accurate segmentation.

In what fields is the "dice coefficient" commonly used?

The "dice coefficient" is frequently used in image segmentation, natural language processing, and bioinformatics to measure the similarity between two samples or segmentations.

What are some alternatives to the "dice coefficient" for measuring similarity?

Alternatives to the "dice coefficient" include the "Jaccard index", cosine similarity, and Tversky index, each with its own nuances in how similarity is calculated.