Due to recent updates, all users are required to create an Altair One account to login to the RapidMiner community. Click the Register button to create your account using the same email that you have previously used to login to the RapidMiner community. This will ensure that any previously created content will be synced to your Altair One account. Once you login, you will be asked to provide a username that identifies you to other Community users. Email us at Community with questions.
Auto Model Clarifications. Help Please
Hi, I have run the auto model on a dataset of soccer teams and their results. Data is classified as: Event Time (Date Stamp), Completition (Like EPL, Champions League), Home Team (Team playing on the home ground) Home score (Goals scored by the home team), Away Team (Visiting team), Score (Goals scored by the visiting team), Classification (Classifying the outcome of score as a big win or other types as defined).
Where in the Auto model I have run do I get to change these parameters e.g. I want to predict the outcome between Barcelona and Espanyol with Espanyol as the home team?
What does Event time: Half Year = 2 or Event Time:half year = 1 mean? How & Why does it change my output?
Where in the Auto model I have run do I get to change these parameters e.g. I want to predict the outcome between Barcelona and Espanyol with Espanyol as the home team?
What does Event time: Half Year = 2 or Event Time:half year = 1 mean? How & Why does it change my output?
Tagged:
0
Best Answer
-
lionelderkrikor RapidMiner Certified Analyst, Member Posts: 1,195 UnicornHi @PyNoob,
These attributes are automatically extracted from your date attribute(s) because by default in AutoModel
the option Extract Date Information is Enabled and then these attributes are one-hot-encoded.
To recover your original attributes and only your original attributes, you have to set :
- Extract date information to Disabled
- Remove Columns with too many values to Disabled (because given that your polynominal attributes have a large number of values, they are removed from the training set.
This way , you can simulate with your original attributes :
Hope this helps,
Regards,
Lionel
7
Answers
Can you please help me answer my question?