For instance, electronic medical records (EMRs) illustrate well the need for data cleaning as it may provide noisy data
containing incomplete information.
Here the regularization operator R[gamma] applied to noisy data
[y.sup.[delta]] is given by
The MKL-BP model keeps the sparsity of [L.sub.1]-MKL model and GMKL model, which only selects useful kernels and makes relatively higher classification accuracy when faced with the noisy data
. We use the Taylor expansion to optimize the problem.
RF effectively deals with noisy data
through (1) bootstrap aggregation, (2) random selection of bands at each node, and (3) learning many variable unbiased decision trees .
The first step is to choose a specific instance selection method for removing some of the noisy data
from the complete subset [D.sub.complete].
Example 1: (a) the input data g(t), (b) the direct computational result with noisy data
From Table 3, we find that the inversion is satisfactory in the case of using random noisy data
, and the inversion errors become small when reducing the noise level.
where [D.sub.n] is the noisy data
set composed by the 15 instances.
Exploiting multiple sparse domains: Reconstructions of real part of image from 5% noisy data
with 15 views, when real and imaginary parts have similar physical boundaries, for different angular coverages: (a) 180[degrees], (b) 150[degrees], (c) 120[degrees], and (d) 90[degrees].
Reconstruction of the heat source with noisy data
for Example 1.
As showed in Figure 1, to evaluate the robustness of mentioned algorithms to noisy data
, all the images were occluded with local and global noise.
Information is comprehended and applied through fundamentally new methods of artificial intelligence that seek insights through algorithms using massive, noisy data