Sentence examples for empirical features from inspiring English sources

Two empirical features of this network are particularly relevant to our forecasting approach: edge innovation and transitivity.

The uncritical use of inductive methods demonstrated by literary historians rejects the hypostatization of terms such as "Renaissance" on the grounds that it promotes a false identity between similar empirical features, which obscures their diversity.

It is an imperative because it commands and constrains us; it is a categorical imperative because it commands and constrains us absolutely, with ultimate authority and without regard to our preferences or empirical features or circumstances.

In this paper, a novel framework for reduced order modeling in reservoir engineering is introduced, where tensor decompositions and representations of flow profiles are used to characterize empirical features of flow simulations.

In the Critique of Pure Reason, imagination is described as "synthesizing the manifold of intuition" under the governance of rules that are prescribed by the understanding: the outcome of this is cognitive perceptual experience of objects as having specific empirical features.

In this relationship, imagination and understanding in effect do what is ordinarily involved in the bringing of objects under concepts, and hence in the perception of objects as having empirical features: but they do this without bringing the object under any concept in particular.

Multiple Empirical Kernel Learning (MEKL) explicitly maps samples into different empirical feature spaces in which the kernel features of the mapped samples can be directly provided.

However, the computational complexity of MEKL with M empirical feature spaces is O MN3) where N is the number of training samples.

The dimensions of the generated empirical feature spaces are approximate to N. When dealing with large-scale problems, MEKL cannot handle them properly due to the severe computation and memory burden.

The proposed MREKLM adopts the random projection idea to map samples into multiple low-dimensional empirical feature spaces with lower computational complexity O(MP3), where P ≪N) is the number of the randomly selected samples.

As shown in Table 2, the highest level of AUC (0.8835) was achieved by using the empirical feature S3 for input encoding.