The phrase "accuracy of the learning" is correct and usable in written English.
It can be used when discussing the precision or correctness of the learning process or outcomes in an educational or training context.
Example: "The accuracy of the learning achieved through this program will be assessed through various evaluations."
Alternatives: "precision of the learning" or "correctness of the learning".
The novelty is to combine the competitiveness of the filter approach which makes it undependable from the nature of the pattern classifier and embed the algorithm within the pattern classifier structure in order to increase the accuracy of the learning phase as wrapper algorithms do.
Hop count and bandwidth of route between probing landmark and target node may also be collected to enforce the accuracy of the learning model [27].
Principal components analysis (PCA) has been performed to obtain new linear combinations, capable to contain the largest possible part of the variance of the original information, without limiting the predictive capability and accuracy of the learning algorithm.
This can be realized by using a learning algorithm to associate the "predictiveness strength" of a network with the assessment of the accuracy of the learning algorithm trained on the network itself.
These experiments confirm the higher accuracy of the machine learning approach with more than 40% improvement, not only over the standard TCP predictor but also when comparing to another well know solution, the Eifel retransmission timer [4].
However, none of the subjects achieved a significant level of accuracy, even with the learning effects in the Gap/Large-food condition.
Averaging over 19 inhibitors and three attribute datasets, the mean accuracies of the learning methods are 79.8% for RF, 78.3% for REPTree, 76.7% for SVM, and 76.0% for SVR.
As a result, the accuracy of the model learned can be computed.
To describe the topographic and tomographic characteristics of normal fellow eyes of unilateral keratoconus cases and to evaluate the accuracy of machine learning classifiers in discriminating healthy corneas from the normal fellow corneas.
We used also the cross-validation standard way to measure the accuracy of a learning scheme on a dataset.
OBJECTIVES: To examine the influences of situational and model factors on the accuracy of Bayesian learning systems.
