How to handle empty fields problems (Not missing data) in a data set
Hello guys.
I have a data set that I collected from 35 companies. one of my attributes is: "do they have this type of plan" and the values will be "Yes" and "No" and my second attribute is "how much is the price of this plan" so for the companies that their first attribute is "Yes" the value would be a number like 30 euros, but for the companies that their first attribute is "No" this filled is empty.
I want to do clustering but because of the empty fields, I can't proceed. I don't want to remove this attribute or any example or even fill up these fields with any missing data techniques, because they are not missing.
is there any technique in Rapidminer to define: if the first attribute is no then ignored the second attribute for that example?
Thank you very much
I have a data set that I collected from 35 companies. one of my attributes is: "do they have this type of plan" and the values will be "Yes" and "No" and my second attribute is "how much is the price of this plan" so for the companies that their first attribute is "Yes" the value would be a number like 30 euros, but for the companies that their first attribute is "No" this filled is empty.
I want to do clustering but because of the empty fields, I can't proceed. I don't want to remove this attribute or any example or even fill up these fields with any missing data techniques, because they are not missing.
is there any technique in Rapidminer to define: if the first attribute is no then ignored the second attribute for that example?
Thank you very much