What Are the Limitations of LOOCV in Cancer Studies?
Despite its advantages, LOOCV is not without its drawbacks. In the context of cancer research, these include:
Computational Intensity: LOOCV can be computationally expensive, especially with large genomic datasets, as it requires training the model multiple times, equal to the number of data points. Variance Concerns: While LOOCV reduces bias, it may increase variance because each training set is almost identical to the others. This can lead to overfitting, particularly in complex models used in cancer genomics. Inadequate for Imbalanced Data: Cancer datasets often suffer from class imbalance, such as a higher number of non-cancerous cases compared to cancerous ones. LOOCV might not effectively address this imbalance, potentially skewing model performance.
