I am working with a pretty large dataset containing 760 rows and arround 58k-60k features and I'd like to perform a feature selection to reduce the dimensionality of those. After stardardising the data I've decide to try with the SelectKBest method from sklearn and I realized that I have to provide a number of features I want to select (named k).
Is there any way of tunning this k parameter? How can I know the proper amount of features to select out of the almost 60k that I have initially?
The dataset contains different cancer patients' genes expressions by the way. Each column is a different gene, that's why I have so many features.