👉 Probe math is a technique used in machine learning, particularly in the context of neural networks, to efficiently identify and analyze the most informative features or regions within an input data. It involves systematically perturbing or "probing" specific parts of the input to observe how much the model's predictions change, thereby pinpointing which features are most critical for the model's decision-making process. This method helps in understanding the model's behavior, diagnosing issues, and guiding improvements by highlighting the aspects of the input that significantly impact the output. By focusing on these key features, probe math aids in debugging, feature selection, and enhancing the interpretability of complex models.
