How to use aggregate function with Toplink

Hi
My question is how can I get the following select when using Toplink-EJB.3:
SELECT MAX(fieldname) FROM tablename;
Thanasi

Hi KAVI PRIYA,
if date is not in cannonical format, how can we change it in BI publisher, then how to calcualte minimum and as well as maximum.
please advise me,
Thanks,
Sri

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How to use aggregate function with Date

Hi All,
I have a group of date from that is it possible to Max and Min of date.
I have tried like this but its errored out <?MIN (current-group()/CREATION_DATE)?>.
I have also tried like this but it doesnt works
<?xdoxslt:minimum(CREATION_DATE)?>
Is it possible to use aggregate function with date values.
Thanks & Regards
Srikkanth

Hi KAVI PRIYA,
if date is not in cannonical format, how can we change it in BI publisher, then how to calcualte minimum and as well as maximum.
please advise me,
Thanks,
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How to use Aggregate Functions during Top N analysis?

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Message was edited by:
user642387

Hi,
Yes, you can do that with aggregate functions.
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hello
can we use analytic function and aggrgate function in same qurey? i tried to find any example on Net but not get any example how both of these function works together. Any link or example plz share with me
Edited by: Oracle Studnet on Nov 15, 2009 10:29 PM

select
t1.region_name,
t2.division_name,
t3.month,
t3.amount mthly_sales,
max(t3.amount) over (partition by t1.region_name, t2.division_name)
max_mthly_sales
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region t1,
division t2,
sales t3
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t1.region_id=t3.region_id
and
t2.division_id=t3.division_id
and
t3.year=2004
Source:http://www.orafusion.com/art_anlytc.htm
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How to use aggregate function on internal table

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types: begin of ty_ftab,
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       comcode TYPE bkpf-bukrs,
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Hi,
try this code,
data : i_sort TYPE TABLE OF slis_sortinfo_alv
w_sort like LINE OF i_sort.
sort it_ftab by cust.
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w_sort-fieldname = 'AMT'.
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w_fcat-tabname = 'it_ftab'.
w_fcat-do_sum = 'X'.
In REUSE_ALV_GRID_DISPLAY FUNCTION MODULE provide the it_sort.
CALL FUNCTION 'REUSE_ALV_GRID_DISPLAY'
* EXPORTING
*    I_INTERFACE_CHECK                = ' '
*    I_BYPASSING_BUFFER                = ' '
*    I_BUFFER_ACTIVE                  = ' '
*    I_CALLBACK_PROGRAM                = ' '
*    I_CALLBACK_PF_STATUS_SET          = ' '
*    I_CALLBACK_USER_COMMAND          = ' '
*    I_CALLBACK_TOP_OF_PAGE            = ' '
*    I_CALLBACK_HTML_TOP_OF_PAGE      = ' '
*    I_CALLBACK_HTML_END_OF_LIST      = ' '
*    I_STRUCTURE_NAME                  =
*    I_BACKGROUND_ID                  = ' '
*    I_GRID_TITLE                      =
*    I_GRID_SETTINGS                  =
*    IS_LAYOUT                        =
*    IT_FIELDCAT                      =
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*    IT_SPECIAL_GROUPS                =
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*    I_SCREEN_END_COLUMN              = 0
*    I_SCREEN_END_LINE                = 0
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Hi,
I am using below code to print min date.
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Hi KAVI PRIYA,
if date is not in cannonical format, how can we change it in BI publisher, then how to calcualte minimum and as well as maximum.
please advise me,
Thanks,
Sri

Oracle Data Mining - How to use PREDICTION function with a regression model

I've been searching this site for Data Mining Q&A specifically related to prediction function and I wasn't able to find something useful on this topic. So I hope that posting it as a new thread will get useful answers for a beginner in oracle data mining.
So here is my issue with prediction function:
Given a table with 17 weeks of sales for a given product, I would like to do a forecast to predict the sales for the week 18th.
For that let's start preparing the necessary objects and data:
CREATE TABLE T_SALES
PURCHASE_WEEK DATE,
WEEK NUMBER,
SALES NUMBER
SET DEFINE OFF;
Insert into T_SALES
(PURCHASE_WEEK, WEEK, SALES)
Values
(TO_DATE('11/27/2010 23:59:59', 'MM/DD/YYYY HH24:MI:SS'), 1, 55488);
Insert into T_SALES
(PURCHASE_WEEK, WEEK, SALES)
Values
(TO_DATE('12/04/2010 23:59:59', 'MM/DD/YYYY HH24:MI:SS'), 2, 78336);
Insert into T_SALES
(PURCHASE_WEEK, WEEK, SALES)
Values
(TO_DATE('12/11/2010 23:59:59', 'MM/DD/YYYY HH24:MI:SS'), 3, 77248);
Insert into T_SALES
(PURCHASE_WEEK, WEEK, SALES)
Values
(TO_DATE('12/18/2010 23:59:59', 'MM/DD/YYYY HH24:MI:SS'), 4, 106624);
Insert into T_SALES
(PURCHASE_WEEK, WEEK, SALES)
Values
(TO_DATE('12/25/2010 23:59:59', 'MM/DD/YYYY HH24:MI:SS'), 5, 104448);
Insert into T_SALES
(PURCHASE_WEEK, WEEK, SALES)
Values
(TO_DATE('01/01/2011 23:59:59', 'MM/DD/YYYY HH24:MI:SS'), 6, 90304);
Insert into T_SALES
(PURCHASE_WEEK, WEEK, SALES)
Values
(TO_DATE('01/08/2011 23:59:59', 'MM/DD/YYYY HH24:MI:SS'), 7, 44608);
Insert into T_SALES
(PURCHASE_WEEK, WEEK, SALES)
Values
(TO_DATE('01/15/2011 23:59:59', 'MM/DD/YYYY HH24:MI:SS'), 8, 95744);
Insert into T_SALES
(PURCHASE_WEEK, WEEK, SALES)
Values
(TO_DATE('01/22/2011 23:59:59', 'MM/DD/YYYY HH24:MI:SS'), 9, 129472);
Insert into T_SALES
(PURCHASE_WEEK, WEEK, SALES)
Values
(TO_DATE('01/29/2011 23:59:59', 'MM/DD/YYYY HH24:MI:SS'), 10, 110976);
Insert into T_SALES
(PURCHASE_WEEK, WEEK, SALES)
Values
(TO_DATE('02/05/2011 23:59:59', 'MM/DD/YYYY HH24:MI:SS'), 11, 139264);
Insert into T_SALES
(PURCHASE_WEEK, WEEK, SALES)
Values
(TO_DATE('02/12/2011 23:59:59', 'MM/DD/YYYY HH24:MI:SS'), 12, 87040);
Insert into T_SALES
(PURCHASE_WEEK, WEEK, SALES)
Values
(TO_DATE('02/19/2011 23:59:59', 'MM/DD/YYYY HH24:MI:SS'), 13, 47872);
Insert into T_SALES
(PURCHASE_WEEK, WEEK, SALES)
Values
(TO_DATE('02/26/2011 23:59:59', 'MM/DD/YYYY HH24:MI:SS'), 14, 120768);
Insert into T_SALES
(PURCHASE_WEEK, WEEK, SALES)
Values
(TO_DATE('03/05/2011 23:59:59', 'MM/DD/YYYY HH24:MI:SS'), 15, 98463.65);
Insert into T_SALES
(PURCHASE_WEEK, WEEK, SALES)
Values
(TO_DATE('03/12/2011 23:59:59', 'MM/DD/YYYY HH24:MI:SS'), 16, 67455.84);
Insert into T_SALES
(PURCHASE_WEEK, WEEK, SALES)
Values
(TO_DATE('3/19/2011 23:59:59', 'MM/DD/YYYY HH24:MI:SS'), 17, 100095.66);
COMMIT;
There are a lot of linear regression models and approaches for sales forecast out on the market, however I will focus on what oracle 11g offers i.e. package SYS.DBMS_DATA_MINING to create a model using regression as mining function and then, once the model is created, to apply prediction function on the model.
Therefore I'll have to go through few steps:
i) normalization of data
CREATE OR REPLACE VIEW t_sales_norm AS
SELECT week,
sales,
(sales - 91423.95)/27238.3693126778 sales_norm
FROM t_sales;
whereas the numerical values are the mean and the standard deviation:
select avg(sales) from t_sales;
91423.95
select stddev(sales) from t_sales;
27238.3693126778
ii) auto-correlation. For the sake of simplicity, I will safely assume that there is no auto-correlation (no repetitive pattern in sales among the weeks). Therefore to define the lag data I will consider the whole set:
CREATE OR REPLACE VIEW t_sales_lag AS
SELECT a.*
FROM (SELECT week,
sales,
LAG(sales_norm, 1) OVER (ORDER BY week) L1,
LAG(sales_norm, 2) OVER (ORDER BY week) L2,
LAG(sales_norm, 3) OVER (ORDER BY week) L3,
LAG(sales_norm, 4) OVER (ORDER BY week) L4,
LAG(sales_norm, 5) OVER (ORDER BY week) L5,
LAG(sales_norm, 6) OVER (ORDER BY week) L6,
LAG(sales_norm, 7) OVER (ORDER BY week) L7,
LAG(sales_norm, 8) OVER (ORDER BY week) L8,
LAG(sales_norm, 9) OVER (ORDER BY week) L9,
LAG(sales_norm, 10) OVER (ORDER BY week) L10,
LAG(sales_norm, 11) OVER (ORDER BY week) L11,
LAG(sales_norm, 12) OVER (ORDER BY week) L12,
LAG(sales_norm, 13) OVER (ORDER BY week) L13,
LAG(sales_norm, 14) OVER (ORDER BY week) L14,
LAG(sales_norm, 15) OVER (ORDER BY week) L15,
LAG(sales_norm, 16) OVER (ORDER BY week) L16,
LAG(sales_norm, 17) OVER (ORDER BY week) L17
FROM t_sales_norm) a;
iii) choosing the training data. Again, I will choose the whole set of 17 weeks, as for this discussion in not relevant how big should be the set of training data.
CREATE OR REPLACE VIEW t_sales_train AS
SELECT week, sales,
L1, L2, L3, L4, L5, L6, L7, L8, L9, L10,
L11, L12, L13, L14, L15, L16, L17
FROM t_sales_lag a
WHERE week >= 1 AND week <= 17;
iv) build the model
-- exec SYS.DBMS_DATA_MINING.DROP_MODEL('t_SVM');
BEGIN
sys.DBMS_DATA_MINING.CREATE_MODEL( model_name => 't_SVM',
mining_function => dbms_data_mining.regression,
data_table_name => 't_sales_train',
case_id_column_name => 'week',
target_column_name => 'sales');
END;
v) finally, where I am confused is applying the prediction function against this model and making sense of the results.
On a search on Google I found 2 ways of applying this function to my case.
One way is the following:
SELECT week, sales,
PREDICTION(t_SVM USING
LAG(sales,1) OVER (ORDER BY week) as l1,
LAG(sales,2) OVER (ORDER BY week) as l2,
LAG(sales,3) OVER (ORDER BY week) as l3,
LAG(sales,4) OVER (ORDER BY week) as l4,
LAG(sales,5) OVER (ORDER BY week) as l5,
LAG(sales,6) OVER (ORDER BY week) as l6,
LAG(sales,7) OVER (ORDER BY week) as l7,
LAG(sales,8) OVER (ORDER BY week) as l8,
LAG(sales,9) OVER (ORDER BY week) as l9,
LAG(sales,10) OVER (ORDER BY week) as l10,
LAG(sales,11) OVER (ORDER BY week) as l11,
LAG(sales,12) OVER (ORDER BY week) as l12,
LAG(sales,13) OVER (ORDER BY week) as l13,
LAG(sales,14) OVER (ORDER BY week) as l14,
LAG(sales,15) OVER (ORDER BY week) as l15,
LAG(sales,16) OVER (ORDER BY week) as l16,
LAG(sales,17) OVER (ORDER BY week) as l17
) pred
FROM t_sales a;
WEEK, SALES, PREDICTION
1, 55488, 68861.084076412
2, 78336, 104816.995823913
3, 77248, 104816.995823913
4, 106624, 104816.995823913
As you can see for the first row there is a value of 68861.084 and for the rest of 16 values is always one and the same 104816.995.
Question: where is my week 18 prediction ? or maybe I should say which one is it ?
Another way of using prediction even more confusing is against the lag table:
SELECT week, sales,
PREDICTION(t_svm USING a.*) pred
FROM t_sales_lag a;
WEEK, SALES, PREDICTION
1, 55488, 68861.084076412
2, 78336, 75512.3642096908
3, 77248, 85711.5003385927
4, 106624, 98160.5009687461
Each row out of 17, its own 'prediction' result.
Same question: which one is my week 18th prediction ?
Thank you very much for all help that you can provide on this matter.
It is as always highly appreciated.
Serge F.

Kindly let me know how to give input to predict the values for example script to create model is as follows
drop table data_4svm
drop table svm_settings
begin
dbms_data_mining.drop_model('MODEL_SVMR1');
CREATE TABLE data_4svm (
id NUMBER,
a NUMBER,
b NUMBER
INSERT INTO data_4svm VALUES (1,0,0);
INSERT INTO data_4svm VALUES (2,1,1);
INSERT INTO data_4svm VALUES (3,2,4);
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commit;
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setting_name VARCHAR2(30),
setting_value VARCHAR2(30)
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INSERT INTO svm_settings (setting_name, setting_value) VALUES
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END;
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BEGIN
DBMS_DATA_MINING.CREATE_MODEL(
model_name => 'Model_SVMR1',
mining_function => dbms_data_mining.regression,
data_table_name => 'data_4svm',
case_id_column_name => 'ID',
target_column_name => 'B',
settings_table_name => 'svm_settings');
END;
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select class, attribute_name, attribute_value, coefficient
from table(dbms_data_mining.get_model_details_svm('MODEL_SVMR1')) a, table(a.attribute_set) b
order by abs(coefficient) desc
-- to get predicted values (Q1)
SELECT PREDICTION(MODEL_SVMR1 USING *
) pred
FROM data_4svm a;
Here i am not sure how to predict B values . Please suggest the proper usage . Moreover In GUI (.NET windows form ) how user can give input and system can respond using the Q1

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it works in SQL plus, but not in report builder!!
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like '%&give_desc%'; ---works in SQL
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Hi Renil,
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How to use aggregate function with Toplink

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