Function Does Not Exist For Decision Tree When Running Tutorial

Feb 8, 2007

When I run the Microsoft tutorial for data mining I get this error when I get to the decision tree part.
I get a similar error for clustering in the same tutorial.
However, The Naive Bayes demo seems fine.
The messages said the project was built and deployed without errors.

Does anyone know how to fix the error:

TITLE: Microsoft Visual Studio
------------------------------

The tree graph cannot be created because of the following error:

'Query (1, 6) The '[System].[Microsoft].[AnalysisServices].[System].[DataMining].[DecisionTrees].[GetTreeScores]' function does not exist.'.

For help, click: http://go.microsoft.com/fwlink?ProdName=Microsoft%u00ae+Visual+Studio%u00ae+2005&ProdVer=8.0.50727.762&EvtSrc=Microsoft.AnalysisServices.Viewers.SR&EvtID=ErrorCreateGraphFailed&LinkId=20476

------------------------------
ADDITIONAL INFORMATION:

Query (1, 6) The '[System].[Microsoft].[AnalysisServices].[System].[DataMining].[DecisionTrees].[GetTreeScores]' function does not exist. (Microsoft OLE DB Provider for Analysis Services 2005)

------------------------------
BUTTONS:

OK
------------------------------

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PLZ HELP ME WITH THE DECISION TREE!!

Apr 16, 2007

I'm having this problem.....



I wanted to use the Decision Tree to show a result..... after i configure the Mining Structures..... and set all the input.... my decision tree shows only until level 2..... i have 3 input and one PredictOnly column.....where is the other input?



Say.... i have House Owner, Marital Status, Num Cars Owned and Number Of Children(PredictOnly)



my Tree only shows All ---- > Marital Status when i input all 3 together...... the other 2 doesn't seems to show.



wat should i do?? my database in SQL Server and the other keys are all correct and deploying finely.....why is this happening.....?



i'm a newbie in this software.......so any pro here can plz help me if there's actually something that i might have missed out along the way.......



Thank you again.........

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Jun 28, 2007

Hi,



Can we represent the Decision Tree in a programatically way in an .NET application? I understand that the outcome of a Decision Tree model can be integrated into an .NET application but not sure if we can also visualize it. Does MS SQL Server support any API to render such a tree?



Thanks a lot!

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Oct 20, 2007

I have got a lot of results like the following two nodes:

All
Existing Cases: 1035298
Missing Cases: 1604
Y = 3,214,966,177,062,520,000,000.000

a >= -0.9822378254 and < -0.7867621803
Existing Cases: 45291
Missing Cases: 17
Y = 9,491,528,329,086,450,000,000.000

Every node of the tree is as odd as this. I checked the training data and found there are 5 bad points with extraordinarily high values of Y. There are over a million points, how can these five points screw up the entire analysis.

I do have good results for other predicted parameters even though they also bad points.

Any tip?

Thanks,

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Microsoft Decision Tree

May 2, 2006

I have an example case below :












Customer Id


Debt Level


Income Level


Employment Type


Credit Risk



1


High


High


Self-Employed


Bad



2


High


High


Salaried


Bad



3


High


Low


Salaried


Bad



4


Low


Low


Salaried


Good



5


Low


Low


Self-Emplyed


Bad



6


Low


High


Self-Employed


Good



7


Low


High


Salaried


Good


My question is how to make a tree from the case above I mean what method we should use to split the tree. (Mannually counting)
I hope anyone could help me by explaining i details.Because i want to make some analysis how microsoft decision tree works exactly.So Please explain me the process to build the tree completely with the method.


Thanks a lot.

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Microsoft Decision Tree

May 16, 2006

Hi again ....i'm trying to understand the works of microsoft decision tree algorithm

I have an example case below :





Customer Id


Debt Level


Income Level


Employment Type


Credit Risk



1


High


High


Self-Employed


Bad



2


High


High


Salaried


Bad



3


High


Low


Salaried


Bad



4


Low


Low


Salaried


Good



5


Low


Low


Self-Emplyed


Bad



6


Low


High


Self-Employed


Good



7


Low


High


Salaried


Good

My question is how about the equations used to determine a split?

Please explain me detailed.

Thanks a lot.

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Dec 5, 2007

Hello,

Im working on my minor project for my Undergrad course.
I have no earlier experience on working with SQL, im the biggest noob if there ever was one.

For a part of my project i have to design a page using php and sql to query from a big student database selected details(Rank, Sex, Branch) and calculate the industrial placement chances and to construct a multiway decision search tree on SQL(im using WAMP server).

This page is supposed to help new students joining the college decide an ideal branch based on past performances and placement record. A new student will enter his rank and relevant details and the from the decision tree an ideal branch(es) with high placement history will be suggested.

My project assignment reads:
"Now from the above prepared data constuct a decision search tree implement it a either using association rules or persistent Objects and store it in secondary storage as shown



Further studies can be done to improve existing decision trees ... data mining bayesian classifier blah blah blah ... "

What i have done till now is create a table in this format:



But this hardly a tree. Rather i had flattened each path of the tree and made it into a table like:
[node] -> [node] -> [node] -> [leaf]

I have tried to read some text on how to do this, but its not making sence and most importantly im not sure what im reading is actually going to help me achieve my project goals. Right now stranded reading random articles. I have to do this within 5 days. I have asked people around here some professionals and teachers, noone seems to have done this before. A little help in direction would be greatly appreciated.

Regards

Anurag

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Feb 19, 2007

Hi

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Thanks,

Nathan



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Jan 9, 2008

Hi,

I'm using SQL Server 2005 Standard Edition, and when I try to process a Decision Tree with more or less 50 input variables I get the following warning:


"Informational (Data mining): Automatic feature selection has been applied to model, TREE_2 due to the large number of attributes. Set MAXIMUM_INPUT_ATTRIBUTES and/or MAXIMUM_OUTPUT_ATTRIBUTES to increase the number of attributes considered by the algorithm."

I've tried to set MAXIMUM_INPUT_ATTRIBUTES to 10 and then there's an error saying: "The 'MAXIMUM_INPUT_ATTRIBUTES' data mining parameter is not valid for the 'TREE_2' model."


Does anyone have a clue of how can I solve it?


Thank you.

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Apr 12, 2006

I have read some sources about microsoft decision tree algorithm like in claude seidman book, paper about scalable classification over sql databases and paper about learning bayesian network. But i still don't understand and i still didn't get the point on how microsoft decision tree algorithm works exactly when splitting an atribut. Because i have read that microsoft decision tree using Bayesian score to split criteria is it true?

Well, anyone could help me to understand about microsoft decision tree algorithm, please give me details explanation with some example(cases).



thanks for anyone help

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Jun 10, 2006

hai ...............all

well i've read in Claude seidmann book about Data mining with microsoft decision, that the statistical techniques employed to build the decision trees include:

Cart, Chaid and C.45.Could anyone explain to me about cart,chaid and c.45? and how the tree statistical techniques influence the decision tree.

thank you so much

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Dec 6, 2007

Hi all,

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Thank you in advance
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Sep 15, 2006

Hi,

I used a decision-tree mining-model to describe and predict fraud. The table contains 1039 records with 775 distinct value of A-number (the calling party). I used 9 columns in the model. SQL Server reports that only 3 columns are significant in predicting the fraud

- BPN_is_too_short (called party-number is too short)
- Duration_is_zero
- Invalid_area_code

The key-column in A-number, and the predicted column is Is_Fraud with the range of values are only 0 and 1. There's no record with NULL (missing-value) in the column Is_Fraud.

Mining Legend shows in the first split
[-] 625 cases of fraud
[-] 150 cases of non-fraud
[-] 0 cases of missing

In addition to that, Mining Legend shows
[-] 79.69% of fraud
[-] 19.64% of non-fraud
[-] 0.67% Missing

Now when I compare those values, they don't match.
(A) 625/775 is 80.645%, not 79.69%
(B) 150/775 is 19.355%, not 19.64%
(C) 0 cases of NULL (missing value) should imply 0% of missing, not 0.67% of missing

Furthermore in one node (with the split on duration_is_zero), there are 541 cases of fraud and 0 cases of non-fraud. This implies the node is leaf-node. However, Mining Legend shows

514 cases of fraud, 99.35%

0 cases of non-fraud, 0.33%

[F] 0 cases of missing, 0.33%


My questions
(1) Why the values don't match like in cases A through C ?
(2) Why the values don't match even in cases D through F when we have no subtree at all ?

I've searched explanation by reading the mathematical reasoning, entropy, Gini index; but it does not answer the discrepancies of those values and percentages in the Mining Legend.

Regards,

Bernaridho

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Access To Decision Tree, Cluster... Charts From C# Or Word

Nov 20, 2007



Hi!
We use SS2005.

a.)
Let's assume you already have defined "mining model" and they are visible in object explorer for Analysis Services.

How to show the picture in an web form (and no I don't want to right click, taking an snapshot of the picture in SSMS or Visual Studio) using c#-api? Alternative: for some time ago I read something about that you can do this in Word, but I can't find the article...

I could see there is an C#-api for Reporting Services so I would expect similar for Analysis Services ;-)

b.)
Lets assume I don't want to go through Visual Studio to creating models. How to store/create new datamining models via C#? And of course: how to force the calculation of the values for node splits etc.?


The solution for "a" will ensure that I always get an actual version of the charts.
Why I ask for "b": Management thinks this will be great for root cause analysis. But I think there is the risk that the
many resulting models, which probably differ will be more confusing than helping.

Thanks

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Aug 24, 2007

Dear All,


If I have a decision tree training work which might last for many days or months. Is it possible to tell the data mining training program to save up the progress at some point? In case the computer hangs or power fail in the middle, the computer can resume the rest of the work at the saving point?

Thanks

Tony Chun Tung Siu

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May 2, 2007

After having built a decision tree model to predict a boolean output attribute using 64-bit SQL Server 2005 (build 9.0.3054), we have observed that predictions for some cases are being done at non-leaf nodes in the tree.



Specifically, after executing a prediction join which returns:


- CaseTable.CaseID
- MiningModel.OutputAttribute
- PredictProbability(MiningModel.OutputAttribute)
- PredictNodeId(MiningModel.OutputAttribute)



and comparing the values of PredictNodeID(MiningModel.OutputAttribute) with the mining model content column [NODE_UNIQUE_NAME] to determine the actual "rule" used to make the case-level prediction.



We have observed that for a subset of cases, predictions are being made at nodes in the tree that are not leaf nodes. Specifically, predictions are being made at a node that is 3 levels deep. The leaf nodes below this inner-tree node are 2 levels further down the tree.



Also supporting the fact that that predictions are being made at this non-leaf node is that the PredictProbability corresponds exactly with the output attribute distribution at this non-leaf node.



In this particular application, we would have obtained better results if the predictions were made at the leaf-nodes.



A few questions:
1. Why are predictions with decision trees made at non-leaf nodes?
2. Is there a way to "force" predictions to occur at leaf nodes via DMX?



Thanks in advance for any information or advice.

- Paul

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Aug 24, 2007

Dear All,


I have a dataminig programming that need to run for days. Is it possibile to speed up the training process by clustering several server by Windows 2003 clustering services? Is it actually that clustering 2 QUAD core computer is almost giving comparable performance as the sum of the speed of two (There must be some overhead, I know). I am actually familiary with the use of clustering. Is it just for making the server farm more reliable or it will collaborate and speeed up the whole training process?

If it is, is there any limit on the number of cluster is in the cluster. What version of Windows and SQL Server do I need to achieve speed up of data mining training process?

Thanks and regards

Tony Chun Tung Siu

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Nov 26, 2007



I am doing some testing with the Microsoft Decision Tree algorithm and I can't get the results I am expecting. At this point I am concerned that my design might be incorrect. Here is my scenario:

Suppose I have a company which sells bikes and I am trying to predict customer satisfaction. Each customer can buy one or more bikes so I set the customer table as the case table and the bike_sale table as a nested table.






Customer Table (Case)

Bike_Sale Table (Nested)


Cust Name

Cust Surname

Cust Satisfaction

Bike Type

Bike Quality


John

Woods

5

Racer

5


Peter

Cole

3

Racer

3


Mountain Bike

4


Joe

Matthews

4

Mountain Bike

4


Tyron

Wright

2

Mountain Bike

2


Josh

Yorke

1

Racer

1


For testing purposes, I hid a pattern in the training data such that the customer satisfaction attribute (the attribute to be predicted) has strong correlation with the bike quality attribute as can be seen in the exemplary data provided.

However, in the data mining model wizard, when I set the Cust Satisfaction attribute as the predictable one and click the Suggest button, the algorithm does not list the bike quality attribute. I also tried setting the Bike Quality attribute as the only input attribute and process the model, but still, no patterns were found. Do you have any suggestions?

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May 18, 2007

We've successfully processed a large decision tree model in SQL Server 2005. When I try to view the tree in the mining model viewer, I get the following error:



TITLE: Microsoft Visual Studio
------------------------------

The tree graph cannot be created because of the following error:

'Exception of type 'System.OutOfMemoryException' was thrown.'.

For help, click: http://go.microsoft.com/fwlink?ProdName=Microsoft%u00ae+Visual+Studio%u00ae+2005&ProdVer=8.0.50727.42&EvtSrc=Microsoft.AnalysisServices.Viewers.SR&EvtID=ErrorCreateGraphFailed&LinkId=20476


The link provides no other documentaiton on the error.



We're using 64-bit SQL on a Dell Workstation running XP-64 with 16GB of memory. From my view of things we aren't close to running out of memory. Since the model processed and the error occurs when viewing the model, is this a problem with Visual Studio and nont necessarily Anlaysis Services?



Thanks in advance.



Nick

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Sep 4, 2007

Hello,
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I tried to increase the size of tempdb but it is imposible, moreover, it starts
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I tried the same model changing the KEY (I assign StudyID as key) then with the same data but 60,000 StudyIDs it is ok, so the mining model is ok (no nested tables, no case, too easy for getting a memory error)...

Please, can anyone recommend a possible solution for this issue?.
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Hi,
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Example:

...
<Node recordCount="600">
<CompoundPredicate booleanOperator="or">
<SimplePredicate field="color" operator="equal" value="red" />
<SimplePredicate field="color" operator="equal" value="green" />
</CompoundPredicate>
<ScoreDistribution value="true" recordCount="200"/>
<ScoreDistribution value="false" recordCount="400"/>
</Node>
...

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How can i import such a node in SqlServer 2005?

Thank you in advance for any help

Chris

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I was doing better without the tutorial!



I can gleen out some concepts but that is all.



If that is all, why have a tutorial?







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