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.
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.......
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?
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.
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.
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.
Can anyone tell me the steps involved in retrieving a model's (decision tree) pmml and use the model content to devleop a web based interface. I am using SQL Server 2005.
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."
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).
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.
I am searching for days for a paper explaining in details the decision tree algorithm that Microsoft uses. It would be very nice if parameters are described in details and the theory basis illustrated. I will be very happy to know in depeth fro this algorithm and how its parameter it affects the results.
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.
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?
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:
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?
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?
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
Query (1, 6) The '[System].[Microsoft].[AnalysisServices].[System].[DataMining].[DecisionTrees].[GetTreeScores]' function does not exist. (Microsoft OLE DB Provider for Analysis Services 2005)
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?
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?
Hello, I have a table (in Access) with about 30 fields and 1,700,000 records. I had created a mining model in AS2005 with only one key (the autonum column called ID) and other attributes marked as Input and/or predict. When processing the model, it finish (after 15 min.) with an error: 3183 "Not enough space in temporal disk" After some search , I encountered that is close related to the memory asigned to the tempdb. I tried to increase the size of tempdb but it is imposible, moreover, it starts with 8MB but it is autosized when needed.
I don't know how to solve this issue. Or, if it is a question of memory/disk space management (I have 100GB of free space in disk).
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?. Many Thanks.
This node shoud contain all cases, whose color is red or green (The Microsoft DecisionTree-Algorithm would build a model with two steps like red/ not red and then green / not green). According to the DMG, this is valid PMML 2.1, but when trying to import the server complains about an unexpected value in the SimplePredicate-tag.
I am in the process of moving databases from a SQL 2005 Standard version to a 2-node 2014 cluster.All of my 2005 databases back up successfully.They all restore without issue except for one database that has a full text catalog. I get this message
Msg 7610, Level 16, State 1, Line 2 Access is denied to "fileStoragedataMSSQLSERVERFullTextCatalog", or the path is invalid. Msg 3156, Level 16, State 50, Line 2 File 'sysft_FTCatalog' cannot be restored to 'fileStoragedataMSSQLSERVERFullTextCatalog'. Use WITH MOVE to identify a valid location for the file. Msg 3119, Level 16, State 1, Line 2 Problems were identified while planning for the RESTORE statement. Previous messages provide details. Msg 3013, Level 16, State 1, Line 2 RESTORE DATABASE is terminating abnormally.
[code]....
I went as far as giving the folder full access to everyone temporarily and received the same error.
I got assignment, how to make it appear in the right order .
/* DROP TABLE EMP SELECT * INTO Emp FROM ( SELECT 'A' EmpID, NULL ManID, 'Name' EmpName UNION ALL SELECT 'MAC' EmpID, 'A' ManID, 'Name__' EmpName UNION ALL SELECT '1ABA' EmpID, 'MAC' ManID, 'Name____' EmpName UNION ALL SELECT 'ABB' EmpID, '1ABA' ManID, 'Name______' EmpName UNION ALL SELECT 'XB' EmpID, 'A' ManID, 'Name__' EmpName UNION ALL SELECT 'BAC' EmpID, 'XB' ManID, 'Name____' EmpName ) b */
hi! I'm just wondering does anyone know how to create an sql command that can search word by word? what i mean is like I have a product with name 'harry potter broom'. I want an sql command where if i type only 'harry broom' this 'harry potter broom' product will show up. Does anyone have any idea? Here's my sql comand: (I'm using asp.net vb script do develop this system) ------------------------------------------------------------------------- query = "select distinct * from product where " & _ "(pname like '%" & keyword & "%' or " & _ "pdesc like '%" & keyword & "%' ) and " & _ "(price >= " & price1 & " and price <= " & price2 & _ ") and status <> 'out of stock' order by price asc" ------------------------------------------------------------------------- Thank you.
Is the word "Name" a reserved word in SQL? look at line 10 of my stored procedure. When I use the word "Name"it is highlited in blue by SQL Server? Note I only list part of the stored proc 1 CREATE PROCEDURE [dbo].[GetXMLPeopleNames] 23 (4 @Status nvarchar(3)5)6 AS7 SELECT8 PersonId,9 PersonDescription,10 Name,11 UpdateDate,12 UpdateAppUser13 FROM14 Customer WHERE Customer.PersonDescription=@Status15 ORDER BY
This database also has a session monitor that logs every access to the database, with a relation to the calendar row id. This way, I can make database access reports, without replicating the date value.
My question is: for a membership table should I follow the same principle and relate member row to the session monitor, which in turn, relates to the calendar or should I put the date just there?
Some of the tables of this database will have to handle some heavy load, both for updating and selecting. This said, my question is should I make a link or put the date just there to extinguish the need to make 2 joins just to know when something was registered / updated? If I only place the relation to know the date I'll have to do something like:
SELECT DATEADD(ss, x.timeOffsetInSeconds, c.dateValue) AS date FROM <somewhere> x JOIN sessionMonitor sm ON sm.id = x.sessionMonitorId JOIN calendar c ON c.id = sm.calendarId
Instead of just doing a select x.lastUpdateDate
How would you gurus usually deal with these situations?
I've decided to put the clustered index on the edit date column on an audit table. As the edit date for a new record is always going to be higher (more recent) than the previous record, the value would go onto the end of the index. So is there still a value in (1) providing a fill specification of less than 100% and (2) padding the index?
I am studying the behavior of 200.000 clients. With the use of decision trees I would like to know if my clients will abandon our service or not. I use a training set of 21.822 clients and I use a predict variable "aband" wich is a discrete variable and it can be 0 or 1. In my training set i have 21.597 cases in which aband is 0 and 255 cases in which aband is 1. Looking at the classification matrix obtained using as input table a testing set (unselected data) I can see that my decision tree doesn't recognize the cases in which aband is 1. Here is the Classification Matrix: Counts for Dati Training on [Aband] Predicted 0 (Actual) 1 (Actual) 0 21597 225 1 0 0
I would appreciate answers to the following doubts I have regarding Decision trees, CONTAINS and using CONTAINS in a DMX query:
1. Does MS decision tree work only off equality/inequality conditions for the nodes? Is it possible to use a predicate as the branch criteria for a node?
2. Can the T-SQL predicate CONTAINS(...) be used in a DMX query? I need to check if a column-value is a substring of another column and create an intermediate column that will enable me to construct a decision tree with the phrase-present/absent branch.
3. Can CONTAINS(...) be used in a select clause? Like -
SELECT CONTAINS(JAT.column1, '"Good day"')
FROM JustAnotherTable;
4. Does CONTAINS(...) support both arguments to be column references? Or, is it mandatory that the pattern (argument #2) has to be a literal string or a variable? E.g.: I need to know the validity of the following expression -
