- Can you briefly explain why overtraining a machine learning model is not a
good idea?
By overtraining a machine learning model by training data too well, we train the model in a way that negatively impacts the performance of the model on new data. It is also referred to as overfitting.
- What is the difference between overfitting and underfitting?
Overfitting refers to overtraining the model, while underfitting refers to a model that can neither model the training data nor generalize to new data.
- What is the difference between an evasion and poisoning attack?
In an evasion adversarial attack, the attacker try many different samples to identify a learning pattern to bypass it; while in poisoning attacks, the attacker poisons the model in the training phase.
- How does adversarial clustering...
