The phrase "a true generalization of" is correct and usable in written English.
It can be used when discussing concepts, theories, or statements that accurately summarize or encompass a broader idea or set of data.
Example: "The theory presented in the paper is a true generalization of the previous research findings, providing a more comprehensive understanding of the subject."
Alternatives: "an accurate representation of" or "a valid summary of".
This calculation is a true generalization of Rumbarger's method and provides an acceptance curve in the load space.
Also this example tells that Theorem 20 is a true generalization of Theorem 1.
Stirling's construction is, as he says, a true generalization of standard utility theory so as to make non-conditioned ("categorical") utility a special case.
By Example 2.3, we know that the definition of strictly G-preinvex functions is a true generalization of that of strictly preinvex functions.
In this paper, we extend the RCOT representation to include the absence of technological options for a sector (i.e., no capacity to produce), a true generalization of the original case (Duchin and Levine [2011]) of 1 through s technological options for a sector to the case of 0 through s options.
The following theorem shows, that the result of Theorem 4.1 is a true generalization of the existing results in literature since the best possible rate for the error, measured in ‖ ⋅ ‖ B s, is equivalent to the best possible rate for the total error from e.g. [13 15].
How do these rules measure up to the goal of arriving at a true generalization?
Crucially, failure to test pure generalization prevents a robust assessment of what component of rat invariant recognition can be ascribed to a spontaneous, purely perceptual evaluation of visual similarity (i.e., to a true generalization process), and what component, instead, depends on learning arbitrary associative relations among trained object views.
Translation by the author: "...Lie's group theory for the integration of equations is not the true generalization of the method applied by Galois for algebraic equations".
While many of the citations in the sample are thus likely to have limited utility for biomolecular event extraction, their inclusion assures unbiased results and a fair test of the true generalization ability of the applied methods.
The leave-one-out method is known to be an almost unbiased estimation of the true generalization error; that is, the performance reported with the leave-one-out method is the most similar to the performance this system would show on an unseen test dataset of infinite length once it is trained on all available data (Vapnik, 1982).
