singleton query agains OLAP based model?

this works, only if my predictable content is not a nested table.

I have a survey like cube:
customer dimension, product dimension and evaluation dimension (good, avg,
bad) and #Evaluations.
I have create a decision tree model using the customer key as the key, what
I want to predict is the evaluation (so a nested table) and also I'm using
the product characteristics in my model (color, type, size etc...)
it's ok.
1 thing is missing here: I have to select the tree what I want to track (ie
select bad, avg or good evaluations) and the model just display "existing"
"missing"
I will prefer to have the 3 evaluation types and the probability to fall
into 1 of these, but it's a small issue.

now, the PredictProbability formula...
the formula doesn't works.

in adv. works I can reproduce it:
SELECT [Subcategories]
, PredictProbability([Subcategories], 2) AS TwoCarsProb
FROM [decision]
NATURAL PREDICTION JOIN
(SELECT 'High School' AS Education,
'Single' AS [Marital Status],
'M' AS [Gender]) AS t


The error is:
Error (Data mining): Only a scalar column reference is allowed in the
prediction function at line 2, column 29.

So how to write a singleton query to use it against the Subcategories
prediction?

Thanks.

Jerome.



"Dejan Sarka" wrote in
message
> Jeje,
>
> I created a DT model on Adventure Works DW demo cube. I used Number Of
> Cars Owned as predictable, Education, Gender and Marital Status as input
> column. I checked the content of the predictable column - when it was read
> from the cube, it was Continuous; I changed it to Discrete. Deployed the
> model, and here is a query that works:
>
> SELECT [Number of Cars Owned],
> PredictProbability([Number of Cars Owned], 2)
> AS TwoCarsProb
> FROM [CubeDT]
> NATURAL PREDICTION JOIN
> (SELECT 'High School' AS Education,
> 'Single' AS [Marital Status],
> 'M' AS [Gender]) AS t
>
> What kind of error do you get? Can you test the way I did?
>
> --
> Dejan Sarka
> http://blogs.solidq.com/EN/dsarka/default.aspx
>
> "Jeje" wrote in message
>
>> Hi,
>>
>> I have created a decision tree DM model from a cube.
>> now I try the singleton query, but how to create the query????
>>
>> the only samples I found works against an RDBMS model.
>> so I'm not sure how to write my query:
>>
>> SELECT
>> flattened
>> [Test Dec Tree].[Performance Levels]
>> ,PredictProbability([?????]) <-- error here
>> From
>> [Test Dec Tree]
>> NATURAL PREDICTION JOIN
>> (SELECT 'Male' AS [Gender],
>> 'Asian' AS [Race Group]
>> ) AS t
>>
>> I have tried a lot of different syntaxes in the predictprobabilty
>> function without success.
>>
>> because it's OLAP based, I only have "existing" and "missing" in my model
>> result, while the samples found are differents.
>>
>> can you point me on a sample anywhere?
>>
>> thanks.
>> Jerome.
>>
>>
>>
>
 >> Stay informed about: singleton query agains OLAP based model? 

ok
I have found
I have to use:
PredictAssociation
instead of PredictProbability


"Jeje" wrote in message

> this works, only if my predictable content is not a nested table.
>
> I have a survey like cube:
> customer dimension, product dimension and evaluation dimension (good, avg,
> bad) and #Evaluations.
> I have create a decision tree model using the customer key as the key,
> what I want to predict is the evaluation (so a nested table) and also I'm
> using the product characteristics in my model (color, type, size etc...)
> it's ok.
> 1 thing is missing here: I have to select the tree what I want to track
> (ie select bad, avg or good evaluations) and the model just display
> "existing" "missing"
> I will prefer to have the 3 evaluation types and the probability to fall
> into 1 of these, but it's a small issue.
>
> now, the PredictProbability formula...
> the formula doesn't works.
>
> in adv. works I can reproduce it:
> SELECT [Subcategories]
> , PredictProbability([Subcategories], 2) AS TwoCarsProb
> FROM [decision]
> NATURAL PREDICTION JOIN
> (SELECT 'High School' AS Education,
> 'Single' AS [Marital Status],
> 'M' AS [Gender]) AS t
>
>
> The error is:
> Error (Data mining): Only a scalar column reference is allowed in the
> prediction function at line 2, column 29.
>
> So how to write a singleton query to use it against the Subcategories
> prediction?
>
> Thanks.
>
> Jerome.
>
>
>
> "Dejan Sarka" wrote in
> message
>> Jeje,
>>
>> I created a DT model on Adventure Works DW demo cube. I used Number Of
>> Cars Owned as predictable, Education, Gender and Marital Status as input
>> column. I checked the content of the predictable column - when it was
>> read from the cube, it was Continuous; I changed it to Discrete. Deployed
>> the model, and here is a query that works:
>>
>> SELECT [Number of Cars Owned],
>> PredictProbability([Number of Cars Owned], 2)
>> AS TwoCarsProb
>> FROM [CubeDT]
>> NATURAL PREDICTION JOIN
>> (SELECT 'High School' AS Education,
>> 'Single' AS [Marital Status],
>> 'M' AS [Gender]) AS t
>>
>> What kind of error do you get? Can you test the way I did?
>>
>> --
>> Dejan Sarka
>> http://blogs.solidq.com/EN/dsarka/default.aspx
>>
>> "Jeje" wrote in message
>>
>>> Hi,
>>>
>>> I have created a decision tree DM model from a cube.
>>> now I try the singleton query, but how to create the query????
>>>
>>> the only samples I found works against an RDBMS model.
>>> so I'm not sure how to write my query:
>>>
>>> SELECT
>>> flattened
>>> [Test Dec Tree].[Performance Levels]
>>> ,PredictProbability([?????]) <-- error here
>>> From
>>> [Test Dec Tree]
>>> NATURAL PREDICTION JOIN
>>> (SELECT 'Male' AS [Gender],
>>> 'Asian' AS [Race Group]
>>> ) AS t
>>>
>>> I have tried a lot of different syntaxes in the predictprobabilty
>>> function without success.
>>>
>>> because it's OLAP based, I only have "existing" and "missing" in my
>>> model result, while the samples found are differents.
>>>
>>> can you point me on a sample anywhere?
>>>
>>> thanks.
>>> Jerome.
>>>
>>>
>>>
>>
 >> Stay informed about: singleton query agains OLAP based model?