🦉 🎤   RapidMiner Wisdom 2020 - CALL FOR SPEAKERS   🦉 🎤
We are inviting all community members to submit proposals to speak at Wisdom 2020 in Boston.
Whether it's a cool RapidMiner trick or a use case implementation, we want to see what you have.
Form link is below and deadline for submissions is November 15. See you in Boston!
Time Series & Feature Engineering Questions
I am trying to solve a sales forcast problem: there is a monthly sales table(attribute:time,sales) and a consumer record table(attribute:order time,A(id),B,C,D) , assuming that sales are related to the consumer's attribute, How should I creat proper feature as input to build a timeseries model to make predictions?
there are many ways to create input by counting instances in different dimensions as input. as follows
var1 =count A when B=b1,
var2 =count A when B=b2
var3 = count A when B=b1,C=c1,D=d1
var4 = count A when B=b1,C=c1,D=d1
How to select proper input for time series prediction from these variable？Is this the right way to creat feature?
Anybody have any ideas? Appreciate a lot for any tips! Would u mind looking at this?:p @Thomas_Ott