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Justyna Jupowicz-Kozak

CEO of Professional Science Editing for Scientists @ prosciediting.com

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predictive capabilities

Grammar usage guide and real-world examples

USAGE SUMMARY

"predictive capabilities" is a correct and usable phrase in written English.
It refers to the ability or potential to make accurate predictions. Example: "The new technology boasts impressive predictive capabilities, accurately predicting customer behavior and market trends."

✓ Grammatically correct

Science

News & Media

Formal & Business

Human-verified examples from authoritative sources

Exact Expressions

60 human-written examples

With more complex systems, our predictive capabilities are sorely tried.

The predictive capabilities of the models are critically assessed.

Similar predictive capabilities were observed when changing the laser wavelength.

Models based on firm physical principles have predictive capabilities.

This highlights the satisfactory predictive capabilities of the presented approach.

Another big star of the BlackBerry 10 keyboard is its predictive capabilities.

News & Media

TechCrunch

"We only focus on personal assistants that provide predictive capabilities," he said.

News & Media

TechCrunch

This includes the inference procedures and excellent predictive capabilities deployed by the techniques.

Some results showed good agreement with the data, whereas other models had poor predictive capabilities.

However, the predictive capabilities of these scores depending on the time after intubation are poorly investigated.

In case of Thailand, Pongsatat et al. (2004) examines predictive capabilities of Ohlson's and Altman's models.

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Expert writing Tips

Best practice

When discussing "predictive capabilities", be specific about what factors contribute to that ability. For example, mention the algorithms, data sources, or expertise that enable accurate predictions.

Common error

Avoid exaggerating the "predictive capabilities" without providing supporting evidence. Always acknowledge the limitations and potential for error, especially in complex systems.

Antonio Rotolo, PhD - Digital Humanist | Computational Linguist | CEO @Ludwig.guru

Antonio Rotolo, PhD

Digital Humanist | Computational Linguist | CEO @Ludwig.guru

Source & Trust

84%

Authority and reliability

4.5/5

Expert rating

Real-world application tested

Linguistic Context

The phrase "predictive capabilities" functions as a noun phrase, where 'predictive' modifies 'capabilities'. It describes the ability or potential of something to make accurate predictions or forecasts. Ludwig AI confirms its usability.

Expression frequency: Very common

Frequent in

Science

78%

News & Media

12%

Formal & Business

10%

Less common in

Academia

0%

Encyclopedias

0%

Wiki

0%

Ludwig's WRAP-UP

In summary, "predictive capabilities" is a grammatically correct and widely used phrase, particularly in scientific, news, and business contexts. It describes the ability or potential to make accurate predictions. Ludwig AI supports its use, confirming its appropriateness in various formal settings. When using this phrase, ensure to provide specific details about the methods or factors that contribute to the stated capabilities and avoid overstating the accuracy without supporting evidence.

FAQs

How can I use "predictive capabilities" in a sentence?

You can use "predictive capabilities" to describe the ability of a system, model, or technology to accurately forecast future events or outcomes. For example: "The model's "predictive capabilities" were evaluated using historical data."

What are some alternatives to "predictive capabilities"?

Depending on the context, you could use phrases like "forecasting abilities", "predictive capacity", or "ability to predict".

Is "predictive capabilities" formal or informal?

"Predictive capabilities" is generally considered a neutral to formal phrase, suitable for academic, professional, and news contexts. It's less common in casual conversation.

What influences the "predictive capabilities" of a model?

The "predictive capabilities" of a model are influenced by factors such as the quality and quantity of data, the sophistication of the algorithms used, and the relevance of the variables considered.

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Source & Trust

84%

Authority and reliability

4.5/5

Expert rating

Real-world application tested

Most frequent sentences: