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View in Help Center (registration required) |
Rulex can solve many types of problems with a full range of tasks.
These types of problems can be divided into the following categories
Problem Type | Description | Available tasks |
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Optimization tasks solve problems related to optimizing a situation, given an objective function and a set of constraints. | ||
In supervised learning |
problems an output attribute is present in the dataset and the target of the analysis is to derive a model that describes the relationship between this output attribute and other input attributes in the dataset. | |
In unsupervised learning |
problems no output variables are present, and examples included in the dataset are partitioned into a |
number of groups (clusters), according to a given measure of similarity: two examples belonging to the same group must exhibit a higher value of similarity than two patterns associated with different clusters. |