Data Science, Machine Learning, Artificial Intelligence, Technology, Data Mining.
optimal number of PCA components for this dataset is 11. This is the number of components required to explain at least 95% of the total variance in the dataset. Choosing 11 components strikes a balance between dimensionality reduction and retaining significant information from the original dataset.