AryaXAI enables users to generate their own models if they do not already possess one.

Upon creating a new project, AryaXAI automatically trains a default model, 'XGBoost_default', for default prediction and explainability. However, users have the option to utilize their own model for explainability through:

1. Uploading own model, or
2. Training a model using AryaXAI's built-in modelling techniques, which include:

• XGBoost
• LGBoost
• CatBoost
• RandomForest
• SGD (Stochastic Gradient Descent)
• Logistic Regression
• Linear Regression
• GaussianNaiveBayes

Users can fine-tune these models and adjust the hyperparameters according to their requirements.

Train Model 

To train a model in AryaXAI:

1. Navigate to the 'ML Models' section from the main menu on left, and select 'Train Model'.
2. Select the desired modelling technique and click ‘Train’
3. Set the Data Configuration to match the settings used during initial data upload. You will need to select the Training tags and Testing tags from the dropdown.
4. Select 'Save initial configuration' and 'Save Feature Encoding' for consistency and accuracy in the model training process
5. Customize the model parameters to tailor the training process according to specific requirements
6. Set the Explainability parameters. Select the Explainer Shape and set the data sample percentage
7. Select the server to run your remote environment on
8. After configuring data and model parameters, select 'Train model' to start the training process

Once training is successful, a comprehensive list of all versions is accessible and listed in the 'Model Versions' tab.

NOTE: A maximum of 10 models can be trained within a workspace. Within a project, only 2 models can be trained. (Considering workspace limitations, a maximum of 5 projects can be created.)

Users can activate the new model manually under ‘Options’ in the ‘Model Versions’ tab. 

Upon activating a model, detailed information becomes available within the 'Model Info' section, providing a comprehensive overview of the model