9i data mining : workspace, extensibility, RAC ??

considering 9i in database data mining features:
1) do the DM algorithms operate on relational workspaces or on analyitical workspaces (where does data reside)
2) is there a possibility of implementing new algorithms (e.g. via something like the Data Cartridge API)
3) how does DM behave in a Real Application Clusters setting: is model building by the DM algorithms performed in parallel
could someone help on this?
Thanks

Darwin operates in an analytical workspace. You must bring the data to Darwin and it must be set up on a two dimensional vector space (1 row per record). You must convert transactional type data to this format
Currently there are no new plans to implement any new algorithms inside of Darwin. We are currently working on the new data mining suite implemented in Oracle 9i called Oracle Data Mining (ODM). This version of data mining does operate within relational spaces uses a multitude of algorithms and handles both transactional and non transactional data
Darwin does not take advantage of RAC because it is not implemented from the database. Darwin takes advantage of it's ability to perform the mining using parallel algorithms. Darwin takes advantage of Clutered hardware (SMP)such as machines like the Sun E6500. ODM does take advantage of RAC.
I hope this helps. If you have any more techncial questions, lease feel free to contact me at [email protected]
Thanks, Richard J. Solari
null

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Data mining is Loading after upgrade from 10.1.0.4 to 10.2.0.4

SQL> select comp_name, version, status from dba_registry;
COMP_NAME
VERSION STATUS
Oracle Ultra Search
10.1.0.4.0 NO SCRIPT
Oracle XML Database
10.2.0.4.0 VALID
Oracle Enterprise Manager
10.2.0.4.0 VALID
COMP_NAME
VERSION STATUS
Oracle Text
10.2.0.4.0 VALID
Oracle interMedia
10.2.0.4.0 VALID
Oracle Expression Filter
10.2.0.4.0 VALID
COMP_NAME
VERSION STATUS
Oracle Workspace Manager
10.2.0.4.3 VALID
Oracle Data Mining
LOADING
Oracle Database Catalog Views
10.2.0.4.0 VALID
COMP_NAME
VERSION STATUS
Oracle Database Packages and Types
10.2.0.4.0 VALID
JServer JAVA Virtual Machine
10.2.0.4.0 VALID
Oracle XDK
10.2.0.4.0 VALID
** How to fix ti..
*** I can find below error in dbua log
===
dbua
Oracle_Server.log 470085 select dbms_java.full_ncomp_enabled from dual;
470086 select dbms_java.full_ncomp_enabled from dual
470087 *
470088 ERROR at line 1:
470089 ORA-29558: JAccelerator (NCOMP) not installed. Refer to Install Guide for
470090 instructions.
470091 ORA-06512: at "SYS.DBMS_JAVA", line 236
470092
470093
470094 Rem If Intermedia, Ultrasearch, Spatial, Data Mining upgrade,
470095 Rem first install JAVAVM if it is not loaded
470096
470097 BEGIN
470098 2 IF dbms_registry.is_loaded('JAVAVM') IS NULL AND
470099 3 (dbms_registry.is_loaded('ORDIM') IS NOT NULL OR
470100 4 dbms_registry.is_loaded('WK') IS NOT NULL OR
470101 5 dbms_registry.is_loaded('SDO') IS NOT NULL OR
470102 6 dbms_registry.is_loaded('EXF') IS NOT NULL OR
470103 7 dbms_registry.is_loaded('ODM') IS NOT NULL) THEN
470104 8 :dbinst_name := dbms_registry_server.JAVAVM_path || 'initjvm.sql';
470105 9 ELSE
470106 10 :dbinst_name := dbms_registry.nothing_script;
470107 11 END IF;
470108 12 END;
470109 13 /
470110
470111 PL/SQL procedure successfully completed.
470112
470113 SELECT :dbinst_name FROM DUAL;
470114
*** Then I can apply 10.2.0.5 PSR ( in data mining is loading)?

You can try de-install and install this component using the following note
Master Note for Oracle Data Mining (Doc ID 1087643.1)

Creating Data Mining PL/SQL Package in SQL Developer

hi,
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can somebody please tell me how to fix this?
thanks!

To verify that Oracle Data Mining PL/SQL Package extension is properly installed, please do the following:
Select Menu Help->About, click on "Extensions" tab. Look for "Oracle Data Mining PL/SQL Package" in the Name column ( you can sort it).
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Oracle data mining module is implemented in database?

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I want to know where the ODM module is implemented.
Is it implemented inside the database?
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Oracle Data Mining is an integrated component of the database engine itself. It is better not to think of it as a data mining module, but rather think of Oracle Data Mining as the Oracle database's built-in machine learning capabilities.
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Invalid Links on OTN Data Mining Page

Hi,
some of the links on the OTN Data Mining Page (http://www.oracle.com/technology/products/bi/odm/index.html) are not working. They end in error 404. This is true for some of the technical information such as the FAQs and the data sheet as well as for the download of the Oracle Data Miner for example.
Best regards,
Marco

Oracle9i Data Mining is an Oracle9i database option - so it's part of the database download. Same with Oracle9i OLAP, but you can download OLAP 9.2.0.4.1 Analytic Workspace Manager or Oracle9i OLAP Web Agent at: http://otn.oracle.com/products/bi/olap/olap.html
Regards,
OTN

Difference between OLAP, Data Mining and Data Warehousing

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I am new to the above topics, but I know oracle DBA very well. I would like to move into the above field. Hence, can anyone tell me the basic oracle softwaare used for OLAP, Data Mining and Data warehousing and also in brief the difference between these three.
I would be great helpfull to me.
Thanks & Regards,
Manoj Mathew

Hi Manoj Mathew,
Check these links to what Oracle has to say about its own software specific for these topics:
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Datawarehousing (tool is OWB): http://www.oracle.com/technology/products/warehouse/index.html
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Data Mining on data specified and filtered by the user in runtime

Hi Experts,
i am new to Data Mining in SAP BI (we are on BI 7.0 SP Level 20). I familiarised myself with APD and Data Mining by reading some interesting and useful threads in this forum and some other resources. Therefore I got a understanding about the topic and was able to create basic data mining model for an association analysis and an corresponding APD for it and write the results into a DSO by using the data source. But for now I was not able to find a solution for a concrete customer requirement.
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So, I have the following questions for these scenarios:
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2.) is it possible to start an APD out of a query, with the particular results regarding filtering?
3.) Can we place a query directly on the data mining results (how?) or do we need to write the data mining results in a DSO first?
4.) What about the performance? Would it be practicable to do the data mining in runtime with the user waiting?
5.) Is the idea realistic at all? Do you have any other idea how to accomplish the requirement (e.g. without APD but with a query, specific filter and conditions)?
Edited by: Markus Maier on Jul 27, 2009 1:57 PM

Hi ,
you can see the example : go to se 80 then select BSP Application ,SBSPEXT_HTMLB   then select tableview.bsp , you will get some idea to be more clear for the code which you have written
DATA: tv TYPE REF TO CL_HTMLB_TABLEVIEW.
tv ?= cl_htmlb_manager=>get_data(
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IF tv IS NOT INITIAL.
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BW Data Mining

Hello!
I need information about the following BW Data Mining topics. Hope, someone can help me?
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Thank you for help!
Regards,
Peter

Hallo!
I need different information about BW data mining.
One thing is, what are typical business scenarios for the different algorithms. So it is easy to find such for decision trees, association analysis and maybe for ABC analysis. But i have little problems to find real scenarios vor weighted score tables and regression analysis. It would be helpful to hear about some.
I have to write a paper for my company about data mining with bw. While we have no experiences in this area I´m looking here for people having.
Also Performance. The problem is not to try out with APD and Data Mining models. But to find experiences with this.
Good or bad performance with this or this algo? Or how can I optimize performance for mass data?
After this I have to design typical business scenarios. Especially for automotive area if possible.
So what the question for me is, what is possible with the algorithms? Where are problems with them?
It would be great if you could provide me with more information about your experiences in this area.
Thanks,
Peter

Data Mining overflow error while loading the mining viewer

I developed a time series model that processes succesfully. The problem I have is that when I try to view the mining model viewer that displays the times series on a chart, I get the error below:
An error occurred while a prediction query was being executed:
'Error (Data mining): An overflow was encountered while converting a predicted value to the '' column, at line 1, column 33. A higher precision data type for the column is recommended.'.
ADDITIONAL INFORMATION:
Error (Data mining): An overflow was encountered while converting a predicted value to the '' column, at line 1, column 33. A higher precision data type for the column is recommended. (Microsoft OLE DB Provider for Analysis Services 2008 R2.)
It looks like the probability value (which is a float data type, for example 0.4452938765) is being stored in a particular column, and the data type of that column cannot contain the range of decimal places that the probability has.
I don't know which column to look for to change its data type like the error messages says. Would anyone have any idea?

Hello,
Thanks for your posting.
It is more related to Data Mining issue in this case. I move the thread to
Data Mining forum for better support. Thanks for your understanding.
Regards,
Elvis Long
TechNet Community Support

OIM 9.1.0.2 - Weblogic JDBC Multi Data Sources for Oracle RAC

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Yes, it's supported. You install against one instance directly of the Rac Server. Then you update the config.xml file and the jdbc resource in your weblogic server with the full rac address. It is documented for installation against RAC. http://docs.oracle.com/cd/E14049_01/doc.9101/e14047/database.htm#insertedID2
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Error (Data mining): The specified mining structure does not contain a valid model for the current task.

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Actual(Service Description).SE value
Actual([Service Description]).[SE value]
Actual(Service Description)
Actual([Service Description])
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Error (Data mining): The specified mining structure does not contain a valid model for the current task.
the following is my mining model structure

Association rules does not allow for cross-validation
Mark Tabladillo PhD (MVP, SAS Expert; MCT, MCITP, MCAD .NET) http://www.marktab.net

Data mining Algorithms in Essbase

Hi,
Just wondering if anyone has used data mining algorithms provided within Essbase. Any thoughts or pointers towards more information will be helpful..
Thanks in Advance !!

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What are the options for me for Data Mining tools?

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mayooran99

I think that Predixion Insight is the easiest tool to use and is very powerful.
All you need to have is Windows OS, Office 2010 or 2013 and internet connection. If you want to look at what you need to do before installing Predixion, I recommend you to take a look at the walkthroughs at
http://predixionsoftware.com/Help/webframe.html#Data%20Modeling%20Walkthroughs.html
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http://predixionsoftware.com/Technology/Predixion-Insight-Download
Tatyana Yakushev [PredixionSoftware.com]

What software do I need to install to get "Data Mining Framework"

Hi,
from edelivery.oracle.com I have downloaded:
1. Hyperion Essbase - System 9 Release 9.3.1.2 Server Windows Installer
2. Essbase Administration Services Release 9.3.1 Windows Installer
I installed both software and I started Administration Services Console, log in etc. Essbase server is working fine.
In Administration Services Console I click on Essbase Servers | localhost | Data Mining | Algorithms and got error:
"message from server [Data Mining Framework is not available. Please contact Administrator].
It looks like I need to install some other software to have access to data mining features. Which software do I need to install?
Regards,
Grofaty

Windows 7 and iCloud Control Panel for Windows v1.1. Also, Apple (Canada) - iCloud - Learn how to set up iCloud on all your

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);
INSERT INTO data_4svm VALUES (4,3,9);
commit;
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CREATE TABLE svm_settings
setting_name VARCHAR2(30),
setting_value VARCHAR2(30)
--settings
BEGIN
INSERT INTO svm_settings (setting_name, setting_value) VALUES
(dbms_data_mining.algo_name, dbms_data_mining.algo_support_vector_machines);
INSERT INTO svm_settings (setting_name, setting_value) VALUES
(dbms_data_mining.svms_kernel_function, dbms_data_mining.svms_linear);
INSERT INTO svm_settings (setting_name, setting_value) VALUES
(dbms_data_mining.svms_active_learning, dbms_data_mining.svms_al_enable);
COMMIT;
END;
--create model
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;
--to show the out put
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

9i data mining : workspace, extensibility, RAC ??

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