This means that the kernel will always try to execute the highest priority task that is ready to run.
This means that each kernel has a fixed share in deciding the class of each test image.
This means that the kernel of the integral operator (47) satisfies the condition of Lemma 3.1 if M > n − m + 6 − β − λ j + − m / p. Hence, by Lemmas 2.4 and 3.1, the operator K j k, l, γ is bounded in L p, q ( D × R ) if l ≥ 1 or 2 k + | γ | > 2 − β − λ j + − m / p. In order to prove this for q > p, we consider the adjoint operator.
It also means that 3D kernel method has learned very well through the membrane proteins training process.
However, the library is limited to the linear case, which means that the dot product kernel has to be used.
As can be seen in Eq. 5, those compound-target combinations in X similar to x⋆, contribute more to the prediction of y⋆, as y is weighted by k T. This means that GP, as a kernel method, mainly infers the value of y⋆ from the most similar compound-target combinations in descriptor space present in the training set, X.
Figure 4 shows that a large area of the global kernel matrix is blue, which means that most values in the global kernel matrix are small.
This means that consecutive elements of the kernel must not in general be placed in the same BRAM.
For example, it is still true that λ = 1 is not an eigenvalue of the generalized Neumann kernel which means that the presented integral equation is uniquely solvable.
In addition, omission of the MC kernel centring means that ncMCE has a time complexity of, and thus is more efficient than the other considered embedding techniques, such as MCE and Isomap, that have a time complexity of.
