Consider a scenario where you are working on developing an anomaly detection system for monitoring the performance of industrial machinery using sensor data.The sensors collect various measurements, such as temperature, pressure, vibration, and other relevant parameters. However, one of the sensors has been malfunctioning and there are many outliers in your data causing your model to overfit the training data. What is the BEST reason that the model is overfitting the training data?The quantity of the training data is too smallThe training data is too "noisy"The model is too complex relative to the data