Multivariate Regression Model Like In Excel

Oct 11, 2007

Hi there,
We need to determine the prediction formula coefficients using the multivariate regression formula as is available in Excel AnalysisTool pack [something like Y = Ax + Bz + C and find A, B, C]. It would be a very "simple" type of analysis that would run on a single table. There does not seem to be an easy built-in SQL function to perform this. However, reading on the web, Analysis Services might be used to do this task? Is there a good sample for a multivariate regression?

Actually, is this a proper approach given the relative simplicity of the calculation? Do we really need to go through the trouble of setting up an Analysis Service solution just for this task?

Thanks in advance

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Multivariate Regression Differences Between Excel And SSAS

Oct 18, 2007

That solved the application problem

However, now we face a different challenge. Running the same data through the SSAS Linear Regression model and the Excel Regression [Data Analysis] tool we get different answers:







Intercept
-3.57537

x
0.242462

z
0.353668
SSAS:
Intercept -2.95188545928199
x 0.201587406861264

z 0.371940525462092

In Excel we set up the Regression analysis using the 95% confidence interval. Is there a concept for confidence interval for linear regression in SSAS?. Since we are doing this for a company that has been using Excel for years, I do not think such a difference in results will be accepted...

Is there anything else we can do to ensure the answers are close? Must we then have to work around and call these calculations from Excel?

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Oct 21, 2007

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Any tip will be greatly appreciated.

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Jan 18, 2008

Hi,

I am trying to create a model using microsoft Linear Regression algorithm. But I want to constrain the coefficient of the parameters to non-negative value. There is concept of bound in SAS where we can specify the range of the coefficient. Does any of the SSAS mining algorithms support restricting the coefficient value?

Thanks,
DMN

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Dec 13, 2007

Hi!
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I got the equation, but I also want to see R squared and R adjusted in same manner as in Excel.
How to achieve that?
Greetings

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Jun 24, 2007

Hello,



This question is regarding the LogRegHelper - "A scorecard for Logistic Regression models" example in sqlserverdatamining Tips and Tricks page. I launched TestLogReg (Analysis Services Database associated with the project) and ran Logistic Regression over that. While the LogReg shows the highest score for IQ (107 - 121), a score of 558, the Logistic Regression shows that Parent Encouragement has the highest score for the case College Plans = 'Plans to Attend'. Can someone verify this and clarify?



I have a few other questions with LR



- In SQL Server 2005 LR Mining Model Viewer "favors" chart, what algorithm is used for generating Scores?



- Can I use this score as a feature selector? Higher score => stronger predictor (input)



- Is the coefficient weight algorithm used in LogReg wrong ?



Thanks



MA

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-p

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create view MyExcel
as
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Hi,



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The format of my data is like this



OrderID Product

100 Bike

100 Helmet

100 Shoes

200 Helmet

200 basketball

200 Bat

300 Shoes

300 Socks



The associate button works perfectly since it asks me which column is the transaction id (orderid) and which column I am trying to predict (product). The advanced create mining model asks me to determine what the columns are...

OrderID=key Product=Input+Predict?



When I run the advance create mining model associate, I get a browser that gives me no rules and the support for only one item itemset (each product but no combination of products).



Does anyone know what I have to do to get it to work like the associate button?

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Hi All,

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Does anyone know if logistic regression supports the following types:


Binomial (standard)

Multinomial (standard)

Conditional

Ordered

Rank-ordered

Nested

Stereotype
Regards,
Joseph

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Is there a similarly simple way to do this in Reporting Services?
Also, the data source for this is OLAP, so if any of you are MDX gurus, is there some regression function to plot all the parallel axis points?


thanks for any insight.
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Apr 22, 2007

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Laura Lerner

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I am also interested in applying the dprobit methodology found in Stata for infinitesimal changes in independent variables.
Has anyone been successful using Stata to implement an SSAS plug-in algorithm?

thank you,
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Oct 19, 2015

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Productnr Productdesc Language
1            product       EN
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I'm thinking of a technical solution, such that when a user logs on, the language is determined and a view determines whether to pick a certain product table specific for a certain language. But then I don't have the opportunity to interchange the different language specific fields in a report (or in my case PowerPivot).

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Apr 25, 2008



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SO we have to set Recovery Model of the database to simple for that period of time, otherwise it will blow up our logs.

Is there any way we can set up log shipping between our production and standby server, but pause it for some time, set recovery model of primary db to simple, execute DTS Bulk Insert Jobs, Bring it Back to Full recovery Model AND finally bring back Log SHipping.

It it possible, if yes how can we achieve this.

If not what could be another DR solution in this scenario.

Thanks Much
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Jan 22, 2007

We are trying to create a model of linear regression with nested table. We used the create mining model sintax as follow :

create mining model rate_plan3002_nested2

( CUST_cycle LONG KEY,

VOICE_CHARGES double CONTINUOUS predict,

DUR_PARTNER_GRP_1 double regressor CONTINUOUS ,

nested_taarif_time_3002 table

( CUST_cycle long CONTINUOUS,

TARIFF_TIME text key,

TARIFF_VOICE_DUR_ALL double regressor CONTINUOUS

)

) using microsoft_linear_regression

INSERT INTO MINING STRUCTURE [rate_plan3002_nested2_Structure]

(CUST_cycle ,

VOICE_CHARGES ,

DUR_PARTNER_GRP_1 ,

[nested_taarif_time_3002](SKIP,TARIFF_TIME ,TARIFF_VOICE_DUR_ALL)

)

SHAPE {

OPENQUERY([Cell],

'SELECT CUST_cycle ,

VOICE_CHARGES ,

DUR_PARTNER_GRP_1

FROM dbo.panel_anality_3002

order by CUST_cycle ')}

APPEND

({OPENQUERY([Cell],

'select CUST_cycle,

TARIFF_TIME,

CYCLE_DATE

from dbo.nested_taarif_time_3002

order by CUST_cycle,TARIFF_TIME')

}

relate CUST_cycle to CUST_cycle

) as nested_taarif_time_3002



The results we got are a model with intercept only. if we don't use the nested variable (the red line) we get a rigth model . (we had more variable ....)

Is there a way to do this regression correctly?

Thanks,

Dror

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Sep 18, 2006

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x1 and x2, where y, x1, x2 are of datatype Float. We try to perform Model Prediction with an Input Table in which some records consist of NULL x2 values. How are the resulting predicted y values calculated?

My guess:

The resulting linear regression formula is in the form:

y = constant + coeff1 * (x1 - avg_x1) + coeff2 * (x2 - avg_x2)

where avg_x1 is the average of x1 in the training set, and avg_x2 is the average of x2 in the training set (Correct?).

I guess that for some variable being NULL in the Input Table, Microsoft Linear Regression just treat it as the average of that variable in the training set.

So for x2 being NULL, the whole term coeff2 * (x2 - avg_x2) just disappear, as it is zero if we substitute x2 with its average value.

Is this correct?



Q2. Model Training -- Using the above example that y regressed on x1 and x2, if we have a train set that, say, consist of 100 records in which

y: no NULL value

x1: no NULL value

x2: 70 records out of 100 records are NULL

Can someone help explain the mathematical procedure or algorithm that produce coeff1 and coeff2?

In particular, how is the information in the "partial records" used in the regression to contribute to coeff1 and the constant, etc ?

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Sep 18, 2006

Q1. Model Prediction -- Suppose we already have a trained Microsoft Linear Regression Mining Model, say, target y regressed on two variables:

x1 and x2, where y, x1, x2 are of datatype Float. We try to perform Model Prediction with an Input Table in which some records consist of NULL x2 values. How are the resulting predicted y values calculated?

My guess:

The resulting linear regression formula is in the form:

y = constant + coeff1 * (x1 - avg_x1) + coeff2 * (x2 - avg_x2)

where avg_x1 is the average of x1 in the training set, and avg_x2 is the average of x2 in the training set (Correct?).

I guess that for some variable being NULL in the Input Table, Microsoft Linear Regression just treat it as the average of that variable in the training set.

So for x2 being NULL, the whole term coeff2 * (x2 - avg_x2) just disappear, as it is zero if we substitute x2 with its average value.

Is this correct?



Q2. Model Training -- Using the above example that y regressed on x1 and x2, if we have a train set that, say, consist of 100 records in which

y: no NULL value

x1: no NULL value

x2: 70 records out of 100 records are NULL

Can soemone help explain the mathematical procedure or algorithm that produce coeff1 and coeff2?

In particular, how is the information in the "partial records" used in the regression to contribute to coeff1 and the constant, etc ?

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Aug 2, 2007

We are seeing a regression bug with the Microsoft JDBC driver 1.2 CTP.

Using this driver, we don't seem to be able to call stored procedures which return a result set, if those stored procedures use temporary tables internally.

The 1.2 CTP driver fails to access such stored procedures in both SQL Server 2000 and SQL Server 2005 databases.
The previous 1.1 driver, suceeds in both cases.

Here is a test case which demonstrates the problem (with IP addresses and logins omitted). The prDummy stored procedure being called is quite simple, and I've copied it below:




Code Snippet

public class MicrosoftJDBCDriverCallingStoredProceduresTest extends TestCase {

// CREATE PROCEDURE [dbo].[prDummy]
// AS
//
// CREATE TABLE #MyTempTable (
// someid BIGINT NOT NULL PRIMARY KEY,
// userid BIGINT,
// )
//
// SELECT 1 as TEST2, 2 as TEST2
// GO

public void testStoredProcedureViaDirectJDBC() {
Connection conn = null;
String driverInfo = "<unknown>";
String dbInfo = "<unknown>";
try {
// Set up driver & DB login...
Class.forName("com.microsoft.sqlserver.jdbc.SQLServerDriver");
String connectionUrl = "jdbc:sqlserver://xxx.xxx.xxx.xxx:1433";
Properties dbProps = new Properties();
dbProps.put("databaseName", "xxxxxx");
dbProps.put("user", "xxxxxx");
dbProps.put("password", "xxxxxx");
// Get a connection...
conn = DriverManager.getConnection(connectionUrl, dbProps);
driverInfo = conn.getMetaData().getDriverName() + " v" + conn.getMetaData().getDriverVersion();
dbInfo = conn.getMetaData().getDatabaseProductName() + " v" + conn.getMetaData().getDatabaseProductVersion();
// Perform the test...
CallableStatement cs = conn.prepareCall("{CALL prDummy()}");
cs.executeQuery();
// If the previous line executes okay, the test is passed...
System.out.println("Accessing "" + dbInfo + "" with driver "" + driverInfo + "" calls the stored procedure successfully.");
}
catch (Exception e) {
// Fail the unit test...
fail("Accessing "" + dbInfo + "" with driver "" + driverInfo + "" fails to call the stored procedure: " + e.getMessage());
}
finally {
// Close the connection...
try { if (conn != null) conn.close(); } catch (Exception ignore) { }
}
}
}
The output of this test under both drivers and accessing both databases is as follows:




Code Snippet

Accessing "Microsoft SQL Server v8.00.2039" with driver "Microsoft SQL Server 2005 JDBC Driver v1.1.1501.101" calls the stored procedure successfully.

Accessing "Microsoft SQL Server v9.00.3042" with driver "Microsoft SQL Server 2005 JDBC Driver v1.1.1501.101" calls the stored procedure successfully.


Accessing "Microsoft SQL Server v8.00.2039" with driver "Microsoft SQL Server 2005 JDBC Driver v1.2.2323.101" fails to call the stored procedure: The statement did not return a result set.

Accessing "Microsoft SQL Server v9.00.3042" with driver "Microsoft SQL Server 2005 JDBC Driver v1.2.2323.101" fails to call the stored procedure: The statement did not return a result set.

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SELECT 'Some more stuff'

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1. How should these fields be interpreted?

2. With Linear Regression, is it possible to get the coefficient values and tests of significance (t-tests?), if they are not part of the output I have pointed to?

Thanks for your help with this?

Sam

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Feb 19, 2008

Hi!

I bought the book €œData Mining with SQL Server 2005€?, but I can€™t find the solution to a problem I have.

I want to retrieve from C# the logistic regression Attribute Value (AV) Scores for the Logistic Regression Algorithm. I can see the Scores from the Microsoft Logistic Regression Viewer (the same of Neural Network Viewer), but I cannot retrieve them via DMX, OLEDB or similar.

Otherwise, is there a formula that I can use to compute that score from the coefficient, support, or probability values of the Attribute Value pair (I can read this values from DMX)?
I can access to them via DMX:

NODE_DISTRIBUTION -> SUPPORT and PROBABILITY ATTRIBUTE_VALUE...

with a query like

SELECT FLATTENED (SELECT ATTRIBUTE_NAME, ATTRIBUTE_VALUE FROM NODE_DISTRIBUTION WHERE VALUETYPE = ... ) FROM [MyModel].CONTENT WHERE NODE_TYPE ....

Thanks in advance

Regards,
Marco

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