🐛[Bug] : Fix model hyperparameter tuning inconsistencies for Elastic Net, Support Vector Regressor, and Random Forest Regressor

[sohampirale]

Issue Description

Multiple machine learning models have hyperparameter configurations defined but are not utilizing them for optimization,
leading to suboptimal performance and potential runtime errors.

app/services/config

app/services/gaze_tracker.py

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Files Affected

• app/services/gaze_tracker.py
• app/services/config.py

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Problems

• Elastic Net and Support Vector Regressor models have hyperparameter configurations defined but are using default parameters instead of optimized ones
• Random Forest Regressor may cause runtime errors due to missing hyperparameter configuration in the config file

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Expected Behavior

Models with defined hyperparameter configurations should utilize them for optimization to achieve better accuracy and
performance, while preventing runtime errors for models without configurations.

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[sohampirale]

Working on this