In this example, we will train an AI model using columns such as: passenger names, survivors, passenger class (Pclass), fares, parents, siblings, sex and age of people who traveled on the Titanic. After training the model, it will classify most important category to least import category. It will also give you measuring analytics such as RME, matrix, etc.
Download the CSV file from the storage folder ( left corner) and if you don't have CSV file upload it to the appropriate storage folder.
Drag and drop an Inject node set the payload to timestamp, name it start training and click done.
Drag and drop a Classification trainer configurator node under Auto AI and name it appropriately to the relevant subject in this example I'm naming it Classification Titanic.
Change the name, project name and choose the dataset on the drop down menu and give it CSV file path and click on Get Data.
Add all the columns that needs to be trained in the selected training column and add what needs to be trained for the target column . In this example passenger class (Pclass), name, sex, age, siblings/spouses aboard, parents/children aboard and fare are trained in the selected training column while survived will be trained in the target column. The setting on here will defer based on your training model and what you want your AI to be trained. when you are ready click done and deploy.
Drag and drop data visualize and model visualize nodes to the flow. Connect all node with console node at the end and click on deploy.
Click on model visualize switch and it will show you decision tree based classifier along with feature importance plot.
Click on data visualize switch and it will show you the overview of the AI/ML variables, correlations and RME and matrix based on the classified AI training.