I have a dataset which contains various clicks which a user did while going through the website. It also contains uniqueid of each user, date and time of the click and their name. Essentially my main aim is to predict what will be next click of the user. For example, if it starts from home then goes to clothing then goes to Denim then from Denim what is the highest probability of its next click?There are 50000 unique click patterns in a month which a user has clicked. Will Markov chain be feasible for such data?
Clicks Time Id
Home,Clothing,Men,Denim,Home 02/10/2018/3:22pm 1234
Home,Kitchenware,glass,purchase 03/10/2018/4:00pm 4567
Home,Clothing,Men,Denim,Purchase 04/10/2018/3:55pm 7891
Home,Clothing,Men 05/10/2018/2:56pm 6789
It is more like Market Basket Analysis.Change your data like:
Home,Clothing,Men,Denim,Home 1234
-->
Home,Clothing, 1234
Clothing ,Men, 1234
Men,Denim, 1234
Denim,Home 1234
After that count the frequency.
If MC could apply to it , calling @Rick_SAS
Don’t miss the livestream kicking off May 7. It’s free. It’s easy. And it’s the best seat in the house.
Join us virtually with our complimentary SAS Innovate Digital Pass. Watch live or on-demand in multiple languages, with translations available to help you get the most out of every session.
Learn the difference between classical and Bayesian statistical approaches and see a few PROC examples to perform Bayesian analysis in this video.
Find more tutorials on the SAS Users YouTube channel.
Ready to level-up your skills? Choose your own adventure.