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kewldude
‎05-25-2020
  • 10 Posts
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Does the test data set need to go through the same data preparation ju...

by Calcite | Level 5 in SAS Data Science
‎11-11-2017 07:14 AM
‎11-11-2017 07:14 AM
Hi, Sorry if this sounds like a stup*d question, but I have two sets of data. 1 is I used as a training/validation set that is imported by the import node. It goes through Drop,Filter,Transform and Partition node (60-40 division for training/validation) before getting fed to different models. now I have another data set that is marked a role of Test, does this data set (which is on an import node) need to go through the same Drop/Filter/Transform nodes before I connect it as an input of the models? I actually tried to do that. I copied the Drop Filter and Transform nodes so it will have its own, but the problem is, its showing me a "Must have at least 1 Train or Raw data set(s)." error. I noticed if i change the role of this import node to train, the error will go away but this node needs to have a role of Test because its a test data set.  ... View more

SAS Enterprise Miner: How to see results in the Test Data set when run...

by Calcite | Level 5 in SAS Data Science
‎11-10-2017 07:04 PM
‎11-10-2017 07:04 PM
I have an Import Data node that imports data from a csv that has 40K rows. The node is assigned a Training role. I ran this node through a partition node that divides the data to 55% training and 45% validation. I connect this node to a decision tree.   I have another Import data node that imports data from a csv that has 4k rows. This node is assigned a Test role. I connect this node to the same decision tree.   Essentially, The decision tree has two inputs. One is from the partition node that has 55%  training and 45% validation. And the other one is from the node that has a Test role.    I ran the decision tree and look at the results. I need to compute for the Recall, Precision, F score measures, so I need the true positive, true negative, false positive and false negative. The decision tree presented me the values from the Training and Validation set. I will use the one from the validation set and also the test set, but how come I can't see the values from the Test set? How can I produce that one? What am I missing?  ... View more

Combine outputs of different platform and use as an input to Ensemble ...

by Calcite | Level 5 in SAS Data Science
‎11-01-2017 04:51 PM
‎11-01-2017 04:51 PM
Hi,   Lets say I used a decision tree and logistic regression nodes in SAS Enterprise Miner and then I have another model produced using SVM in Python . How can I get the python output and use it in SAS EM with the intention of using the output of the decision tree, logistic regression and this SVM from Python as an input to the Ensemble Node?   I know SAS EM has an SVM node and the probable answer to my question is why use Python when you can use SAS EM and its SVM node. Still, the question is if i want to combine outputs from a different platform/language and use it in SAS EM, how do I go about doing that? Any samples?     ... View more

Re: Difference of Roles for File Import Node in SAS Enterprise Miner

by Calcite | Level 5 in SAS Data Science
‎11-01-2017 03:45 PM
‎11-01-2017 03:45 PM
Is hold out data set the same as validation set or test set? Its been confusing at times seeing these terms being used interchangeably... ... View more

Correct way of using the Ensemble Node

by Calcite | Level 5 in SAS Data Science
‎11-01-2017 03:43 PM
‎11-01-2017 03:43 PM
Hi,   I just want to ask what is the correct way of using the Ensemble Node. I have three models Decision Tree, Neural Net, Logistic Regression. All of the outputs of these models are connected to the Ensemble Node. The Ensemble Node is connected to the Model Comparison Node. I believe this is the usual way of using the Ensemble Node, but then I have seen some configuration that connects the 3 models to the ensemble node, at the same time, each of these models output is connected to the model comparison node together with the output of the ensemble node. Essentially, whats happening is there are 4 inputs (output of decision tree, neural net, logistic reg, ensemble) to the model comparison node. Question is, which is the correct way of doing this?   ... View more

Difference of Roles for File Import Node in SAS Enterprise Miner

by Calcite | Level 5 in SAS Data Science
‎10-25-2017 04:24 AM
‎10-25-2017 04:24 AM
Hi. Sorry if this seemed to be a stupid question, but I just wanted to get some clarification on the Role values available for the File Import node. "Train" and "Validate", I understand them, but I would like to know the difference between "Test" and "Score" role. This is in relation to a decision tree that I made, basically i have a file import node set to train role and connected to a decision tree, then that decision tree is connected to a score node. Then I have another data set (that I dont know how to set the role for, is it test? or is it score?) that is on a file import node that will be connected to the same score node. I asked my professor about it, but the answer given to me was, he is used to using score than test role. I just don't buy his answer without an exact explanation.      ... View more

Re: Handling "Unknown" variables in Enterprise Miner

by Calcite | Level 5 in SAS Data Science
‎10-23-2017 05:38 AM
‎10-23-2017 05:38 AM
Just wondering if anyone can provide a quick example that I can use as a basis? ... View more

Handling "Unknown" variables in Enterprise Miner

by Calcite | Level 5 in SAS Data Science
‎09-12-2017 10:06 PM
‎09-12-2017 10:06 PM
I'm not sure if this is the right forum, but I have just started using Enterprise Miner in my Predictive Analytics subject, so I thought of posting my problem here.    You see I have a dataset that has some categorical cariables which has a value "unknown". This is not blank or missing per se, but an actual category level of a variable (i.e. marital status variable with single, married, divorced, unknown as the possible levels of the variable).   Going through the basic Enteprise Miner tutorial, I had a look at the Replacement and Impute node, but I'm not sure how to go about it.   What I wanted to do is to replace all these unknown values with something like the most frequent marital status value that was used in the dataset.    Care to nudge me in the right direction? ... View more

Decision Tree under sampling/ over sampling using SAS Enterprise Miner

by Calcite | Level 5 in SAS Data Science
‎09-07-2017 01:35 AM
‎09-07-2017 01:35 AM
Hi. I'm a first time poster and I'm a newbie in the world of data mining. I have to be honest, I'm working on an assessment that requires me to produce different decision trees using SAS Enterprise Miner by coming up with different configuration. I'm also quite new in using Enteprise Miner and had just gone through the Intro to SAS Enterprise Miner pdf.  My dataset (which is an imported csv) is composed of bank data (e.g. age, education, job, housing loan, personal loan, consumer index, precious outcome of marketing campaign etc) that intends to predict whether a client will sign up for a lon or not, so I have a signup class with yes and no as the expected result. I noticed in my whole dataset which is around 40k rows, most of the results are No, only around 10% are yes. Based on my readings, this is called an unbalanced data set and I won't get a good model out of this. I did some more readings and I read somewhere that I need to undersample the "No" results in order to oversome this over representation. I raised this to my professor and ask him how I can do it in Enterprise Miner, but he just ignored me, so I'm left to do it on my own. My question is how do i go about this using SAS Enterprise Miner 13.1?  ... View more
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