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:
- Uploading own model, or
- 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:
- Navigate to the 'ML Models' section from the main menu on left, and select 'Train Model'.
- Select the desired modelling technique and click ‘Train’
- 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.
- Select 'Save initial configuration' and 'Save Feature Encoding' for consistency and accuracy in the model training process
- Customize the model parameters to tailor the training process according to specific requirements
- Set the Explainability parameters. Select the Explainer Shape and set the data sample percentage
- Select the server to run your remote environment on
- 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.
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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