data is finite

USAGE SUMMARY

The phrase "data is finite" is correct and usable in written English.
You can use it when discussing the limitations or boundaries of data in a particular context, such as in research or data analysis. Example: "In our study, we must remember that data is finite, which means we cannot draw conclusions beyond the available information."

✓ Grammatically correct

Science

Human-verified examples from authoritative sources

Exact Expressions

2 human-written examples

However, at a very low SNR, this is not so when the length of the observed data is finite.

EURASIP Journal on Advances in Signal Processing

CGH data is finite signal.

BMC Genomics

Human-verified similar examples from authoritative sources

Similar Expressions

58 human-written examples

where U S is the signal subspace spanned by eigenvectors corresponding to major eigenvalues of matrix R, U N is the noise subspace spanned by eigenvectors corresponding to small eigenvalues of matrix R. In practical calculation, the received data are finite, so the covariance matrix R can be estimated as R ^ = 1 L ∑ i = 1 L Z t Z H t, (5).

EURASIP Journal on Advances in Signal Processing

It should be mentioned that this bias cannot be removed when the length of the preamble and the OFDM data symbol is finite and it serves as a lower bound of the iterative estimator.

EURASIP Journal on Advances in Signal Processing

In a typical pattern classification scenario the available data set D is finite and is defined as D = { ( x i, y i ) } i = 1 N, where x i ∈X; y i ∈Y and N refers to the size of the given sample data.

Journal of Cheminformatics

[Approx1] "they cannot make predictions that are immediately comparable to observed data": All observed data is of finite precision so it can be claimed that comparing model results to   observed data is often (but not always) feasible.

F1000Research

Theorem 3.4 Let u 0 ∈ H s, s > 3 2, and T be the maximal time of the solution u to (1.1) with the initial data u 0. If T is finite, we obtain lim t → T ( T − t ) min x ∈ S u x ( t, x ) = − 1.

Advances in Difference Equations

Any result is represented in the computer as finite sequence of bits, which can be considered the value of a mathematical function of all the input data, which are finite bit sequences as well.

F1000Research

We assume that the initial data E | X ( 0 ) | 2 is finite and X ( 0 ) is independent of W ( t ) and N ( t ) for all t ≥ 0. Under these conditions, we note that equation (1.1) has a unique solution on [ 0, + ∞ ), see [10, 11].

Advances in Difference Equations

If the distribution of the data is (approximately) known, finite sample size eigenvalue distributions have been determined for several data distributions.

EURASIP Journal on Advances in Signal Processing

Important factors affecting the efficiency and performance of NNC are (i) memory required to store the training set, (ii) classification time required to search the nearest neighbor of a given test pattern, and (iii) due to the curse of dimensionality it becomes severely biased when the dimensionality of the data is high with finite samples.

Information Fusion

Expert writing Tips

Best practice

When discussing data analysis or modeling, explicitly acknowledge that "data is finite" to set realistic expectations for the scope and generalizability of your findings. This helps avoid overstating conclusions based on limited information.

Common error

Avoid drawing sweeping conclusions without acknowledging that "data is finite". Overgeneralizing from a limited dataset can lead to biased or inaccurate results. Always consider the potential for unseen data to alter your conclusions.

Linguistic Context

The phrase "data is finite" functions as a statement of fact or acknowledgement of a limitation. It is used to qualify discussions in various fields, particularly science and statistics, where the bounded nature of datasets impacts analysis and interpretation. Ludwig AI validates the common use of the phrase.

Expression frequency: Rare

Frequent in

Science

100%

Less common in

News & Media

0%

Formal & Business

0%

Encyclopedias

0%

Ludwig's WRAP-UP

In summary, the phrase "data is finite" is a grammatically correct and usable expression, primarily found in scientific and academic contexts. Ludwig AI confirms its validity. It serves to acknowledge the inherent limitations of datasets and promotes cautious interpretation of research findings. Alternative phrases like "data is limited" or "data has boundaries" can be used interchangeably depending on the desired nuance. Remember to consider the implications of finite data when drawing conclusions from your analysis to avoid overgeneralization.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

data is limited

Highlights that data availability is restricted or not comprehensive.

the dataset is finite

Specifies that the collection of data is limited.

data is bounded

Emphasizes the existence of limits or boundaries to the data.

data has limitations

Focuses on the presence of inherent shortcomings or restrictions within the data.

data is restricted

Suggests that access to or the scope of the data is limited.

the data has boundaries

Emphasizes that there are defined limits beyond which the data does not extend.

data is constrained

Indicates that the data is restricted by certain conditions or factors.

data's scope is limited

Highlights that the extent or range of the data is not extensive.

data is not infinite

Directly contrasts the idea of data being unlimited.

data is exhaustible

Implies that the data can be completely used or consumed.

FAQs

What does it mean when we say "data is finite"?

Saying that "data is finite" means that the amount of data available for a particular analysis or problem is limited. It is not infinite or unlimited, which can affect the conclusions or models derived from it.

How does the fact that "data is finite" impact data analysis?

The finite nature of data impacts analysis by limiting the scope and generalizability of findings. It necessitates careful consideration of potential biases and the possibility that unseen data could alter the results. Techniques like cross-validation and sensitivity analysis can help mitigate these issues.

What are some alternative ways to say "data is finite"?

You can use alternatives like "data is limited", "data is bounded", or "data has limitations" depending on the specific context and nuance you want to convey.

How can I account for the limitations of "data is finite" in my research?

Acknowledge the finite nature of your data in your methodology and discussion sections. Use techniques appropriate for limited datasets, such as regularization or Bayesian methods. Avoid overstating your conclusions and consider the potential impact of unobserved data.