Analyzing and Optimizing Results
When you have obtained your first results in Rulex, you will probably want to analyze and optimize them.
There are may tasks that allow you to do just this on the many structures produced by Rulex tasks.
For further information
Structures can also be converted into datasets and vice-versa to perform in-depth analysis operations.
For more information on this see the section Converting Structures
Available tasks
Task Name | Structure | Description | Corresponding Page |
|---|---|---|---|
Rule Manager | Rules | Inspects, manipulates and optimizes sets of rules.
Input Tasks This task can be used with any of the following LLM tasks that generate rulesets:
| |
Rule Viewer | Rules | Graphically displays rules, and retrieves information such as their importance, the relationship between classes of output attributes with respect to input attributes.
Input Tasks This task can only be used with rules generated by the Classification LLM task.
| |
Feature Ranking | Rules | Graphically displays the importance of attributes within a class values within specific attributes.
Input tasks The task can be used only with rules that originate from one of the following tasks:
| |
Merge Rules | Rules | Merges rules from multiple computations. | |
Optimize Ruleset | Rules | Improves the generation of predictive rules through a series of constraints. | |
Association Manager |
| Analyzes association and replacement rules, using filtering or sorting operations, computing statistics or creating plots. The task is very similar to the Data Manager, but is designed specifically for replacement and association rules. | |
Find/Replace | Rules | Replaces values that can be modified with new values to improve the outcome of the analysis. | |
Itemsets/Sequences Manager |
| Analyzes, filters and sorts frequent itemsets and sequences in a similar way to the Data manager task.
Task input You must have produced clusters, itemsets or sequences in your process via one of the following tasks:
| |
Confusion Matrix | Model | Computes and visualizes the performance of any classification method.
Input tasks The task can be used with any classification task, but must be proceeded by an Apply Model task that tests the classification results on data.
| |
Apply Model | Model | Applies a model generated in Rulex on data.
Input tasks Models can be made up of classification and regression rules and clusters, and the task can consequently be used after any classification, regression or clustering task.
|