The job should be simple just run the [login to view URL] file using pandas.
1) Run the scikit-learn built in library to do the svm-radial basis function (RBF) algorithm to divide the data set into X_training for training and y_training for label into 5 cross validation. (my problem is i don't know which one to choose as label and which one as the training). Also generate X_test and Y_test accuracy
2) Do the same thing with the dataset but this time use knn as the algorithm for ML and do 7 cross validation.
Paper that i want to imitate from is below.
[login to view URL]
Accuracy rate has to match with the paper such as almost 96%. This .csv file was downloaded from the paper.
8 freelanceria on tarjonnut keskimäärin 179$ tähän työhön
Hi there, my name is Daniel. I have over 3 yrs of experience working with scikit-learn to develop machine learning solutions. I can imitate the paper and deliver quality work. I can guarantee an excellent job.
Hi, We will need to discuss a bit more on below doubts I have. 1) There are no column headers hope you are aware of headers. 2) Explain relationship between [login to view URL] and [login to view URL]