Machine Learning: Some notes about Cross-Validation

K-fold cross-validation is one of the most used cross-validation methods. In this method, k represents the number of experiments(or fold) that I want to try in order to test and train my data. For example, suppose that we want to make 5 experiments(or performance) with our data composed of 1000 records. So during the first experiment, we test or validate the first 200 records and then we train the remaining 800 records. When the first experiment is finished I obtain a certain accuracy.