Plugin Algorithms | Several algorithms get customized to the domain they are applied to resulting in unconventional or new algorithms. For example, a hybrid approach on association clustering can benefit determining relevant associations when the matrix is quite large and has a large tail of irrelevant associations from the cartesian product. In such cases, some from clustering could be done prior to association to determine the key items prior to this market-basket analysis. | IT service requests are notoriously susceptible to being opened with variations even when pertaining to the same category. These service requests do not have pre-populated fields from a template, and everyone enters values for inputs that differ from one to another. Using a hybrid approach, it is possible to preprocess these requests with clustering before analyzing such as with association clustering. |
Simultaneous classifiers and regions-of-interest regressors | Neural nets algorithms typically involve a classifier for use with the tensors or vectors. But regions-of-interest regressors provide bounding-box localizations. This form of layering allows incremental semantic improvements to the underlying raw data. | IT Service requests are time-series data and as more and more are opened, specific time ranges become as important as the semantic classification of the requests. Using this technique, underlying issues can be discovered as tied to outages. The determination of root cause behind a handful of service requests is valuable information. |
Algorithm Implementations:
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