Leave one out Cross validation using sklearn (Multiple CSV)
Leave One Out Cross Validation is just a special case of K- Fold Cross Validation where the number of folds =  the number of samples in the dataset you want to run cross validation on.

For Python , you can do as follows:

from sklearn.model_selection import cross_val_score
scores = cross_val_score(classifier , X = input data , y = target values , cv = X.shape[0]) 


Here , cv = the number of folds . As cv = number of samples here , we will get Leave One Out Cross Validation.
The length of list(scores) will be equal to number of samples in input data.