I have 52 CSV files in a folder. I want to build a model based on this data. That's why I want to Leave one out cross-validation on these data. How can I do this using sci-kit learn in python?
I tried from sci kit document and also search many resources.
import glob import numpy as np import pandas as pd from sklearn.cross_validation import LeaveOneOut path=r'...................\Data\New design process data' filelist=glob.glob(path + "/*.csv") loo=LeaveOneOut() for train,test in loo.split(filelist): print("%s %s" % (train, test))
But it showed errors.
init() missing 1 required positional argument: 'n'
I am new in python as well as sci-kit learn. If anyone can help me, It would be a great convenience.