kkboudin
Mechanical
- Oct 25, 2007
- 3
Hi,
I have a large quantity of data from a test site where 500 parameters are measured every minute and I have acces to 2 years of this data. I want to model 5 of these parameters in function of the most important other parameters (The model has 5 Output parameters and I want to select the best parameters to model these 5 output parameters). The data set is noisy, clouded and some parameters are redundant. I am looking for a method to determine the parameters which are higly correlated with the 5 parameters I have to model. I know I can just calculate the correlation coeficcients. But I dont think this is suffucient.
I have examined a method called Principal Component Analysis but I dont think there is a way to Calculate Principal Components in function of the 5 parameters I wish to model. Here comes my first question, is there a method wich calculates Principal Components in function of other parameters?
I am currently examining feature selection but I don't find good references about this method. Can someone give advice on this method?
If you have any other method to calculate the best variables to model with in function of the output parameters.
Thanks in advance, Regards
I have a large quantity of data from a test site where 500 parameters are measured every minute and I have acces to 2 years of this data. I want to model 5 of these parameters in function of the most important other parameters (The model has 5 Output parameters and I want to select the best parameters to model these 5 output parameters). The data set is noisy, clouded and some parameters are redundant. I am looking for a method to determine the parameters which are higly correlated with the 5 parameters I have to model. I know I can just calculate the correlation coeficcients. But I dont think this is suffucient.
I have examined a method called Principal Component Analysis but I dont think there is a way to Calculate Principal Components in function of the 5 parameters I wish to model. Here comes my first question, is there a method wich calculates Principal Components in function of other parameters?
I am currently examining feature selection but I don't find good references about this method. Can someone give advice on this method?
If you have any other method to calculate the best variables to model with in function of the output parameters.
Thanks in advance, Regards