12-08-2015
frak
Calcite | Level 5
Member since
11-07-2015
- 7 Posts
- 0 Likes Given
- 0 Solutions
- 0 Likes Received
-
Latest posts by frak
Subject Views Posted 2214 12-01-2015 01:26 PM 2220 12-01-2015 12:40 PM 2250 11-28-2015 10:59 AM 10264 11-09-2015 01:19 PM 10273 11-09-2015 12:36 PM 10313 11-07-2015 11:27 AM 10322 11-07-2015 11:02 AM -
Activity Feed for frak
- Posted Re: Interactions without principal effects on SAS Data Science. 12-01-2015 01:26 PM
- Posted Re: Interactions without principal effects on SAS Data Science. 12-01-2015 12:40 PM
- Posted Interactions without principal effects on SAS Data Science. 11-28-2015 10:59 AM
- Posted Re: Using cross-validation in Enterprise Miner; on SAS Data Science. 11-09-2015 01:19 PM
- Posted Re: Using cross-validation in Enterprise Miner; on SAS Data Science. 11-09-2015 12:36 PM
- Posted Re: Using cross-validation in Enterprise Miner; on SAS Data Science. 11-07-2015 11:27 AM
- Posted Using cross-validation in Enterprise Miner; on SAS Data Science. 11-07-2015 11:02 AM
12-01-2015
12:40 PM
Ok 🙂 thanks a lot, now i understand why using the setting "two Factor Interaction" or not my output was the same! 🙂
Althought my problem is that that a model with only interactions (in my opininion) has no sense: interaction has sense only if also principal effects are significant in the model. So now my new question is:
how could i tell EM to use a hierarchic procedure while it puts variables into the model?
I mean how can i tell it FIRST to enter significant principal effects and only THEN interactions (between princ. eff. wihch had entered as significant)?
I imagine that i should modify the settings in "use default selection values" in model selection panel but, what should i modify in particular?
Again, thank you in advance!
... View more
11-28-2015
10:59 AM
Hi all, i've a problem: i'm using a node of regression in SAS EM WORKSTATION 12.1; I'm using a cross-validation method and my aim is getting a logistic regression with the possible insertion of significant interactions. So my settings are: principal effect--> YES 2 factors interactions -->yes polynomial terms -->yes maximum degree of polynomial terms = 2 regression kind = logistic regression selection method= stepwise selection criterion= crossvalidation error (this bcs i'm using cross-validation) The final model proposed is: Intercept Gravidanze*Pedigree IMP_BMI*IMP_Diastolica IMP_BMI*IMP_Glucosio IMP_Insulina*Pedigree (for the full output see the attachment stattalk.txt) So all my effects are interactions of quantitative variable ad no principal effect seems to be significant. I'm trying to find an explanation to this output.. can someone help me? But that's not all, because if i modify settings and sat up "2 factor interactions-->NO" (I do not modify others settings) and i run the node i obtain the same output.. ..so i think there is something wrong, but can someone tell me what? i wait for some advice Smiley Happy thank you in advance!
... View more
11-09-2015
01:19 PM
Oh, it seems you were waiting for me ahah .. so fast 🙂
Yes, i could use a data partitioning node but i would lose the benefits of crossvalidation: i would like not to divide my dataset...
..in any case thanks you a lot 🙂
... View more
11-09-2015
12:36 PM
Daaa Daan I'm back again, and i've new dubts..
As Miguel, (thank you again Miguel!) recommend me, I used Start and End node to obtain cross-validation.
So, as expected ,using a 10 fold crossvalidation, i obtained 11 different dataset (10 with 9/10 of data and 1 complete), for each of which EM calculated a model. That's OK.
BUT, in my studies I learnt (maybe) that also in k-fold cross-validation i've finally a validation dataset, which is the result of the "sum" of scores of each model (created on (k-1)/k of data) on the ramaining 1/k of data, AND this doesn't happen in EM: so i don't have a validation dataset.
This is a big problem for me, because, as I understood, i need a validation to evaluate the presence of overfiffing in my model, don't I? How could i tell if there's overfitting or not only looking training datasets?
Someone could tell me what is wrong?
Again, sorry for my terrible english, and thank you in advance!
... View more
11-07-2015
11:02 AM
Hi, this is my problem: I've got a dataset on which i've to apply the technics of data mining. Because my dataset is small (about 700 obs.) i thought not to use external validation, but cross-validation (10 fold); Although i don't now how to make it on Enterprise Miner: I mean, when i specify some models i can't find the way to tell Enterprise Miner to use cross-validation. I E in trees models there is the explicit option "execute crossvalidation yes/no" but in other type models i can't find it. So someone can help me to use cross-validation with regression and MBR models? I hope i've written something you can understand. Thank you
... View more