For more details on the dataset, see Dataset section.
Enter the code for the Model Objective.
The code should be unique for each model objective.
Enter the name and description for the Model Objective.
Select one of the column/feature as the target variable for the models which
needs to be trained/uploaded.
Select the Type from options such as Classification ,
Regression, or Others.
Classification: Classification is a process
of finding a function which helps in dividing the dataset into classes based on
different parameters. The task of the classification algorithm is to find the
mapping function to map the input(x) to the discrete output(y).
Regression: Regression is a process of
finding the correlations between dependent and independent variables. The task
of the Regression algorithm is to find the mapping function to map the input
variable(x) to the continuous output variable(y).
Others:If the Type is not Classification or Regression,
select this option.
Enter the description for the Model Objective.
Click Create.
The Model Objective is created and displayed in the
Model Objective Summary screen.