Sign Up to our social questions and Answers Engine to ask questions, answer people’s questions, and connect with other people.
Login to our social questions & Answers Engine to ask questions answer people’s questions & connect with other people.
Lost your password? Please enter your email address. You will receive a link and will create a new password via email.
Please briefly explain why you feel this question should be reported.
Please briefly explain why you feel this answer should be reported.
Please briefly explain why you feel this user should be reported.
I have this “weird data” format type. It goes like this.
[v1, v2, v3, v4... vn] where n>0
now each “v” is a 2*1 vector. Example:
v3 = [time stamp, event]. (type [<string>, <string>])
Ok now my question is, what kind of classifier can I use, or is it better to use, with this format of data? For example, will the KNN be better or the perceptron algorithm?
Just want to get an idea on how to move on.
The classification algorithm depends on your task. If you have training data, you can use Bayesian classifier, Neuron Network, Support Vector Machine, k-NN or perceptron. If you just want to discover the structure of your “weird data”, try k-means first.