The phrase "a reasonable generalization of" is correct and usable in written English.
It can be used when discussing a conclusion or inference that is drawn from specific instances or data that is deemed to be fair or logical.
Example: "Based on the survey results, we can make a reasonable generalization of the preferences of our target audience."
Alternatives: "a fair assumption of" or "a logical inference from".
The cost and the availability of funds to cover it will of course depend on local circumstances, though a reasonable generalization might be that face-to-face contact will be less costly in studies with fewer participants.
Finally, the model is shown to yield ∼0.85 AUC ROC when tested on sequences with only 0.65 sequence identity, indicating a reasonable generalization capacity to evolutionary distant sequences.
Although test data were derived from a limited set of whole genome shotgun data, and results suggested reasonable generalization, it will be of considerable interest to train our classifiers on a sufficiently large training set derived from whole genome shotgun studies as this is likely to be the standard approach for cancer genome interrogation in the coming years.
This study presents a cerebellar model articulation controller NN (CMAC NN) classifier, which has the advantages of very fast learning, reasonable generalization ability and robust noise resistance.
The use of an encoding scheme, inspired by the work of Willems [25], proved to be quite conservative in the extraction of the EC (typically 1 20), exhibiting reasonable generalization performances and avoiding overfitting.
Cross validation is a well known method that provides a reasonable estimate of the generalization error of a prediction model.
In other words, the modified gravity, which represents a classical generalization of general relativity, becomes reasonable alternative.
Besides having a satisfactory trade-off between discrimination and generalization, the model also allowed patients be divided into a reasonable number of classes, most characterized by well separated confidence intervals of prognostic probabilities.
