Before proceeding, please ensure that the data you want to analyze is saved in separate CSV files for input variables (explanatory variables) and output variables (response variables).
For both the input and output files, it is essential to have a header row with column names adhering to the following requirements:
– Column names should start with an alphanumeric character and subsequent characters may include alphanumeric characters, white spaces ( ), underscores (_), and hyphens (-).
– Refrain from using only symbols, spaces, or numbers in column names, as they may lead to errors.
– Any text data within the columns, other than the column header, can result in an error.
If you plan to utilize Auto-Tuning, it is advisable to have a minimum of approximately 20 data entries for a smoother analysis process.
It is common practice to set aside about 10% of the training data as test data and use it to verify the accuracy of the trained AI model.
l About 90% of the records (actual training data): used to train the AIl About 10% of the records (test data): used to verify predictive performance by comparing the AI’s predictions with the test data
