The phrase "accuracy for the task" is correct and usable in written English.
It can be used when discussing the precision or correctness required to complete a specific task or assignment.
Example: "The accuracy for the task is crucial to ensure the results are reliable and valid."
Alternatives: "precision for the task" or "correctness for the task".
Our prototype of semantics-aware employee expenses analytics and reasoning, experimented with 191,346 unique Accenture employees in 2015, has demonstrated scalability and accuracy for the tasks of explaining and predicting abnormal expenses.
In this study, we find that (i) polyharmonic splines (PHS) in conjunction with supplementary polynomials provide a very simple way to defeat stagnation (also known as saturation) error and (ii) give particularly good accuracy for the tasks of interpolation and derivative approximations without the hassle of determining a shape parameter.
The analysis revealed a main effect of task (F1,15 = 20.02, P < 0.001), indexing higher accuracy for the alphabet task as well as interactions between task and PM (F1,15 = 13.63, P < 0.005) and PM and stimulus phase (F1,15 = 4.71, P < 0.05).
Taking a closer look at those approaches, we also noticed that 1in-GEINet yielded the best accuracy for the identification task (i.e., rank 1 identification rate), while the Siamese yielded the best performance for the verification task (i.e., EER).
We show how we improved the classification components and feature selection in order to achieve high-level throughput and high-level accuracy for the classification task of big data.
A wrapper method is designed to provide better classification accuracy for the prediction task in the preliminary step.
Force-matching accuracy for the knee task was correlated with location of peak activation in the motor cortex when the data were analysed with both groups combined and when data for each group were analysed separately.
Schuman and Bergler (2006) [18] do not include an interpretive component, but they demonstrate the ability to produce accurate syntactic attachment for post-nominal prepositional phrases using a corpus-based approach, achieving 82% accuracy for this task.
Thus, accuracy for this task was estimated by examining consecutive overlapping sequences of 4 responses.
This indicates that the proposed method can achieve satisfactory accuracy for the face recognition task.
