The described real-time PCR assay is fast (~2 3 hours, if DNA extraction is included), simple to perform and results are easy to interpret, features which make it applicable in the routine of clinical microbiology laboratories.
As a result, one obtains a horizontal view, which is usually hard to interpret: features in the optimal set, which is found by best performance on the development set, are usually a mixture of all groups.
However, L2-regularization tends to keep most weight elements to be non-zeros, which makes it difficult to interpret features from the resulting weight vector.
These data have also been used to help interpret features found within the structures of the stem cell transcription factor Nanog (18) and the Drosophila Bicoid DNA complex (19).
Another possible solution is to use L1-regularization that tends to make most weight elements to be zeros, which makes it easier to interpret features from the resulting weight vector.
Hence, oncologists should look for a specific statement within the pathology report regarding the presence or absence of chemotherapy response and it's degree; if there is no comment regarding chemotherapy effect they should ask the reporting pathologist to go back and review the case, rather than interpret features such as necrosis and inflammation as indicative of response.
Theoretical predictions are also successfully used to identify and interpret characteristic features in the NEXAFS spectra that arise from specific vacancy sites present at oxygen deficient surfaces.
Some newly interpreted features include a north-trending structure, and three north-west trending structures that segment the north-east trending orogen.
Therefore, one can suffer from interpreting features from learned weights.
One common regularization is L2-regularization, which keeps most elements in the weight vector to be non-zeros; therefore, one can suffer from interpreting features from learned weights.
This paper set out with the goal of exploring whether the statistical demands of naturalistic motion estimation could provide a useful lens for interpreting features of Drosophila's behavior and neural circuitry that push beyond the canonical HRC.
