The Altair Community is migrating to a new platform to provide a better experience for you. In preparation for the migration, the Altair Community is on read-only mode from October 28 - November 6, 2024. Technical support via cases will continue to work as is. For any urgent requests from Students/Faculty members, please submit the form linked here
Preparing data for pattern recogintion
Contributor I
Hello again, I'm still new to rapidminer, so please be passioned 
Currently I am writing my master thesis in electrical engineering. I guess using rapidminer fits perfectly for some excellent simulating results. I guess I could write something about the simulation in my thesis. But first of all here some information about my data: I have a database resp. a set of training data, that looks like this:
There are multiple containers (1..n). Each container has multiple measurements (1..m). Each measurements consists of x-y-z data. The first measurement can have 100values for each component x,y and z. The second measurement might have 130 values for each x-y-z component...
container-1 [ measurement-1[x,y,z], measurement-2[x,y,z], measurement-3[x,y,z], ..., measurement-m[x,y,z]]
container-2 [ measurement-1[x,y,z], measurement-2[x,y,z], measurement-3[x,y,z], ..., measurement-m[x,y,z]]
...
container-n [ measurement-1[x,y,z], measurement-2[x,y,z], measurement-3[x,y,z], ..., measurement-m[x,y,z]]
On the other hand I have on measurement, which will be tested against the training database to classify, if my measurement-x attends to container 1,2, .. n...
My question is, how do I have to setup my CSV or Excel file for the database?! And how can I test a measurement against my database set? I think I have to use x-validation, right? If you need more information about my project, dont hesitate and ask
Currently I am writing my master thesis in electrical engineering. I guess using rapidminer fits perfectly for some excellent simulating results. I guess I could write something about the simulation in my thesis. But first of all here some information about my data: I have a database resp. a set of training data, that looks like this:
There are multiple containers (1..n). Each container has multiple measurements (1..m). Each measurements consists of x-y-z data. The first measurement can have 100values for each component x,y and z. The second measurement might have 130 values for each x-y-z component...
container-1 [ measurement-1[x,y,z], measurement-2[x,y,z], measurement-3[x,y,z], ..., measurement-m[x,y,z]]
container-2 [ measurement-1[x,y,z], measurement-2[x,y,z], measurement-3[x,y,z], ..., measurement-m[x,y,z]]
...
container-n [ measurement-1[x,y,z], measurement-2[x,y,z], measurement-3[x,y,z], ..., measurement-m[x,y,z]]
On the other hand I have on measurement, which will be tested against the training database to classify, if my measurement-x attends to container 1,2, .. n...
My question is, how do I have to setup my CSV or Excel file for the database?! And how can I test a measurement against my database set? I think I have to use x-validation, right? If you need more information about my project, dont hesitate and ask
0
Answers
Regarding the database, look at the CSVReader or ExcelReader operators. They can read in Excel sheets.
X-Validation or cross-validation is a method of testing the strength of a model. It's not used in classifying new data.