What is data dependency in machine learning?

What is data dependency in machine learning?

Data dependency in machine learning refers to the reliance of a model's performance on the quality and quantity of the data used for training. It highlights how the data influences the learning process.

Can you give me an example of data dependency?

Sure! For instance, if a model is trained on biased data, it may produce biased predictions. This shows how the data's characteristics directly affect the model's outcomes.

How can I reduce data dependency in my models?

You can reduce data dependency by using techniques like data augmentation, regularization, and ensuring diverse and representative training datasets.

What are the risks of high data dependency?

High data dependency can lead to overfitting, where the model performs well on training data but poorly on unseen data, limiting its generalization.

Are there any tools to analyze data dependency?

Yes, tools like SHAP and LIME can help analyze feature importance and understand how different data points influence model predictions.