Regression tasks#

Regression is a modelling technique able to predict a continuous target variable. The objective data-driven predictions, provided by regression tasks, support the decision process by making it easier to evaluate future risks and opportunities.

Rulex Factory provided users with regression tasks and integrates them with regression algorithms. These are essential as the software applies them to solve supervised learning problems.

Note

An algorithm is a precise set of rules, typically used to solve a class of specific problems, that produces an output or a decision.

It is recommended to split the data into two parts before using any Regression task:

  • the training set, used to identify patterns in the data and build the model. It is usually made of the 70-80% of the data available.

  • the test set, used to assess the accuracy of the model. It is usually made of the 20-30% of the data available.

  • the optional validation set, which can be used for tuning the model parameters.

In Rulex Factory, users can divide their datasets by using two different tasks:

If users want to apply the model to the data, they should remember to add an Apply Model task after the chosen regression task.

Supervised learning#

In supervised learning problems, the dataset contains an output attribute that is the target for developing a model describing its relationship with other input attributes. The output attribute that defines the target class or category is a nominal attribute. For example, regression algorithms can be used to predict whether house prices are going to increase.

Regression tasks layout#

Rulex Factory’s Regression tasks share similar features and a common layout.

Depending on the selected task, users will find three or four tabs:

  • the Options tab, where users can choose the attributes they will work on and with. According to the chosen task, it is divided into one or two tabs: Basic and Advanced.

    • In the Basic tab, according to the chosen task, users will find the following panes with their own specific options and features:

      • the Attributes list, which is always displayed on both the Options and the Advanced tab.

      • the attribute drop area.

      • One pane where users are able to customize different options.

    • In the Advanced tab, users can configure additional options.

Note

Please note that the options contained in the Advanced tab are different for each Regression task.

  • A tab where users can visualize the corresponding spreadsheet or plot for each task. Depending on the task used, this tab will have different names. They can be: Models, Coefficient, Points, and Monitor.

  • the Results tab, where users can visualize the computation information. It is divided into two tabs:

    • the General info, where users can find general information.

    • the Result Quantities, where users can find more detailed information.