What are the Challenges Associated with High Dimensionality?
One of the primary challenges associated with high dimensionality is the so-called "curse of dimensionality." As the number of variables increases, the amount of data required to accurately model the system grows exponentially. This can make it difficult to obtain reliable results without extensive experimentation and computational resources. Furthermore, high dimensionality can lead to overfitting in machine learning models, where the model becomes too complex and performs poorly on new data.
