Why is training data essential for machine learning models in threat recognition?

Training data is crucial for machine learning models in threat recognition because it provides the necessary examples from which the models learn to identify patterns and make predictions. By feeding the model a diverse and representative dataset, the model can recognize subtle variations and correlations that indicate potential threats. This learning process is what enables the model to generalize and accurately identify similar patterns or threats in new, unseen data. In essence, without sufficient and high-quality training data, the model would lack the foundational knowledge needed to perform effectively in real-world scenarios, resulting in reduced accuracy and effectiveness in threat detection.