lower accuracy for

USAGE SUMMARY

The phrase "lower accuracy for" is correct and usable in written English.
It can be used when discussing the performance or effectiveness of a method, model, or system in relation to its accuracy in a specific context. Example: "The new algorithm showed lower accuracy for predicting outcomes in complex scenarios compared to the previous version."

✓ Grammatically correct

Science

Human-verified examples from authoritative sources

Exact Expressions

29 human-written examples

In addition, our study reports higher accuracy compared to prior efforts for legitimate users, and lower accuracy for naive adversaries.

Human-centric Computing and Information Sciences

However, the number of arcs in such networks may be low, which results in lower accuracy for the deformation estimation.

Journal of Modern Transportation

Do people who report more inconsistent details exhibit lower accuracy for the consistently recalled material that they produce?

Cognitive Research: Principles and Implications

To address these deficits (faster speed and lower accuracy) for the at-risk group, these fourth-grade girls were randomly assigned word problems under two experimental conditions (highlight vs. nohighlight) within a counterbalanced condition- and form-order design.

Contemporary Educational Psychology

Compared to the results of simulated ICESat-2 data, MABEL data achieve lower accuracy for ground and canopy heights in terms of root mean square error (RMSE), which may partly result from the inconsistency between MABEL and reference data.

Remote Sensing of Environment

Additional file 1: Figure S2 shows relatively high accuracy for blocks at lower altitude (90 120 km) above land, and lower accuracy for high-altitude blocks (240 270 km) above the ocean for Case 1 and Case 4. This is consistent with the results of the classical checkerboard test discussed earlier (Figs. 2, 3).

Earth, Planets and Space

Human-verified similar examples from authoritative sources

Similar Expressions

31 human-written examples

Nearest neighbour, linear and cubic interpolation all show lower accuracies for all descriptors compared.

EURASIP Journal on Image and Video Processing

The relatively lower accuracies for the detection of damaged urban areas are discussed in "Madhyapur Thimi and Gangabu" section.

Earth, Planets and Space

Adult FEC had lower accuracies for most breeds compared to FEC1 and FEC2.

BMC Genomics

Despite lower accuracies for GS than PS, the Bulmer effect appeared stronger for the former than the latter.

Genetics, Selection, Evolution

When predicting CB (scenarios 6 and 7; Table 5), the addition of PB populations resulted in lower accuracies for AFI and TNB but higher accuracies for LBW and LVR.

G3: Genes, Genomes, Genetics

Expert writing Tips

Best practice

When comparing the accuracy of different methods or models, clearly specify the metric used to measure accuracy (e.g., root mean square error, F1-score) to provide a concrete basis for comparison.

Common error

Avoid attributing "lower accuracy" to a single cause without considering multiple contributing factors. Accuracy can be influenced by data quality, model complexity, and parameter tuning; address these aspects in your analysis.

Linguistic Context

The phrase "lower accuracy for" functions as a descriptive modifier, typically used to qualify a noun or pronoun. It specifies a reduced degree of correctness or precision in a particular situation, application, or context. As shown in the Ludwig examples, this is often applied in scientific and technical domains.

Expression frequency: Common

Frequent in

Science

100%

Less common in

News & Media

0%

Formal & Business

0%

Ludwig's WRAP-UP

In summary, the phrase "lower accuracy for" is a grammatically sound and frequently used expression, particularly within scientific and technical fields. It serves to denote a diminished level of precision or correctness in specific scenarios. As Ludwig highlights, this phrase is best suited for formal contexts where a clear communication of performance limitations is essential. When using "lower accuracy for", ensure that the context is well-defined, and consider alternatives such as "decreased precision in" or "reduced correctness in" to refine your message. The Ludwig AI confirms that the phrase is correct and usable, but care should be taken to avoid oversimplifying the causes of reduced accuracy in technical writing.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

decreased precision in

Focuses on the reduction of precision rather than general accuracy.

less reliable in

Simpler alternative indicating a reduction in reliability.

reduced correctness in

Highlights a decrease in the state of being correct.

compromised trueness in

Emphasizes reduced fidelity or faithfulness to a true value.

less fidelity in

Similar to "compromised trueness", but more concise.

diminished reliability in

Emphasizes the reduction in the consistency of results.

inferior exactness in

Highlights the inferiority in achieving exact results.

impaired validity in

Indicates compromised validity or trustworthiness of results.

degraded performance regarding

Focuses on how overall performance is degraded with respect to the task.

poorer performance in

Broader term, focuses on outcome rather than direct accuracy.

FAQs

How can I use "lower accuracy for" in a sentence?

You can use "lower accuracy for" to describe situations where a method or model performs with reduced precision in a specific context. For example, "The new algorithm showed "lower accuracy for" predicting outcomes in complex scenarios."

What are some alternatives to "lower accuracy for"?

Alternatives include phrases like "decreased precision in", "reduced correctness in", or "diminished reliability in", depending on the specific nuance you want to convey.

What factors typically contribute to "lower accuracy for" a particular task?

Factors may include insufficient data, inadequate model complexity, noisy input data, or the presence of confounding variables. Addressing these can potentially improve accuracy.

Is "lower accuracy for" always a negative outcome?

Not necessarily. In some applications, a slight reduction in accuracy might be acceptable if it leads to other benefits, such as increased speed or reduced computational cost. It depends on the specific trade-offs involved.