An example that deals with k-means classification along with Leave One Out Cross Validation
The two outcomes for the given input data “germancredit_info.csv,” are success and failure, which represent defaulting on the loan and not defaulting, respectively. You need to perform logistic regression by considering the features of the loan and characteristics of the borrower as the explanatory variables.
After this, you are required to perform k-means classification with the help of three continuous variables—duration, amount, and instalment.
Finally, take help of the cross-validation method to determine the percentage of identification that happens correctly.
For the given example the percentage of identification that happens correctly is 65.36% and the k-means classification looks like this:
