Hello everybody,
I am interested in mining association rules field
I have found some posted statements but I didn't undertand them. I need your help badly.
Just tell from where should I start?
Thanks alot
When i use the MS association rules ,i don't know how it is worked on the background .I stuy the Fp-Growth algorithm , but there're some questions , I don't kown what's the meaning of transcation database. who can give me one example ? thanks .I know we can store the data in relation database,but in basket Analysis ,how a transaction stroed in relation database?
View 3 Replies View Related1) I use the identifier of transaction and attribute in one table.
Do I can to build a association rules structure without the use of the nested tables?
I tried - did not turn out...
2) As it is necessary to use a main and child table, can not build a prediction query.
When I try to add the predict column in a criteria/argument (Field=PredictSupport), i'll given message:
"Nested table column cannot be used as an argument in a data mining function."
I can not use other columns, because they are not predicable.
Hi there,
it has been a long i'm trying to execute Microsoft Association Rules on my database.
I solved memory leak problem now, but i still can't understand output rules.
Database contain all the italian student who took a degree last year. Here in Italy, they have to compile a summary where they speak about universitary experience. ie: they talk about experience with teachers (pointage from 1 to 5); they says if they want to continue in the universitary field or not, and so on.
Most of the rules, says:
Int_Stud=1-2, RapDoc>4
Int_Stud is the column where i store student intention to continue university. 1 means they want to go on, 2 means they do not want to continue to study. So, this rules has no sense, because it relates all the student (in my mind): the one who wants to continue university and the one who do not want to.
I think problem is that visual studio 2005 and analysis service has no understanding of Int_Stud world, they've no idea that Int_Stud can have just 2 values and that they're opposite each other. Is there a solution to this problem? Can i discretize this column?
Even if I know not to have perfect english, I hope to be understandable
I note that there exist three web viewers for data mining algorithms, namely, DMNaiveBayesViewer, DMDecisionTreeViewer and DMClusterViewer. How come there are no viewers for association rules (itemsets, rules, dependency network)? Can you suggest any alternative way of showing such valuable information in a web application?
View 1 Replies View Related
I understand Mr. MacLennan's explanation provided at http://forums.microsoft.com/MSDN/ShowPost.aspx?PostID=282651&SiteID=1 and appreciate the time he took to explain how importance works. However, like the user with username "sang", I also ran the data in BI 2005 and got the same results listed by the aforementioned user. I did this using the following data:
donut
muffin
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
n
y
n
y
n
y
n
y
n
y
etc.
The rule muffin -> donut has an importance of -0.105302438, which is not the same as Mr. MacLennan's results. I tried switching the roles of a and b in a -> b and using different bases on the logarithms. I don't get the result of -0.105302438 with any of these. I also tried to calculate importance with a small data set I have and can't get the results using Mr. MacLennan's explanation with that data set either. Any thoughts on the descrepancy?
Hi
I am doing the Market basket analysis for a retailer using association rule. The whole data set is huge which contains grocery, clothes and books etc. If I want to check out the relationship between several different clothes brands, (e.g. LEVI'S and adidas), should I just remove all the grocery and books transactions, use the subset which only contains clothes transactions to re-run the association rules? Is this gonna work?
Thanks in advance!
Hi
I got a question about the data preparation of market basket analysis.
There are always some transactions with only one single SKU product. It seems that these kind of transactions have nothing to do with association. Shall I just exclude them or what?
Thanks in advance.
Hello,
I want to score my data by only the assoziation rules I filtered in Mining-Model-Viewer.
Is this possible?
I recognized that MiningModel Predictionquery uses the generated Model (all rules).
Is there any way to influence the model at generating time.
Thanks a lot.
Hi,
I specified the point to solve my problem but I did not understand why MS SQL Server didn't recognize the Association parameters I but in. It uses the Minimum_Probability I put in, but the Minimum_Importance i wrote didn't care it, it use the default value.
I want to paste a screenshot here but it isn't possible. By the way I'm using the evaluation version, which should be same as the enterprise edition.
Hope for a soon answer.
Best Regard
I need to create a set of cases for a project that uses the Microsoft Association Rules algorithm to make recommendations for products to customers. My question is: the set of scenarios must include all transactions of customers for training?. or is it sufficient some percentage of total transactions? If i do not use all transactions of customers, could be that the algorithm does not consider some products in their groups or rules and could not make recommendations about these?
thanx
Diego B.
I've set up an association rules mining model on SQL Server 2005.
Below is the output for the "rules" tab in the model viewer:
0.457 0.480925197502775 BAKERS BASKET = Existing -> FR ORANGE JUICE = Existing
0.423 0.467835626151174 ONE EGG = Existing -> FR ORANGE JUICE = Existing
0.416 0.42489020548496 GRANOLA PARFAIT = Existing -> FR ORANGE JUICE = Existing
0.416 0.344523279228151 CROISSANT = Existing -> REG CAPPUCCINO = Existing
0.430 0.338244068974039 PAIN AU CHOC = Existing -> REG CAPPUCCINO = Existing
0.424 0.332652863071932 FR ORANGE JUICE = Existing, REG LATTE = Existing -> REG CAPPUCCINO = Existing
The problem is that I can't seem to reduce the minimum probability below .42 to view more rules.
I've considered that it might be becuase these are the only rules discovered, however I know quite a bit about the data and I would excpect many more associations.
The data is transactional in the format
TransactionID, ItemID
Hello,
I'm new to analysis services and hopefully this is a quick & easy question. I have a couple of quite large (163,000 tuple) tables with columns essentially representing a bit vector. I would like to mine for association rules but the number of '1' values are very, very sparse and they are the only objects of interest. How can I get more control over the algorithm---that is, how can I stipulate that the state of the column must be '1' to be considered? Any help or direction to the proper documentation would be great.
Hi!
I'm building a mining model wiht MS Association Rules. After processing this model, the result includes some rules(example):
E = Existing, C = Existing -> B = Existing
F = Existing -> E = Existing
C = Existing, B = Existing -> E = Existing
F = Existing -> B = Existing
B = Existing, A = Existing -> C = Existing
F = Existing, B = Existing -> E = Existing
F = Existing, E = Existing -> B = Existing
D = Existing -> A = Existing
C = Existing -> A = Existing
E = Existing, A = Existing -> B = Existing
I want to buid a query that has two or more items on the left of the rules, example: E = Existing, C = Existing -> B = Existing
->I want to buid a query to predict that: when a customer buy 'E' and 'C' then he likely buys 'B'
Hi
I read the paper of sequence clustering. It seems that the major application of the algorithm is for the web site. I was just thinking that can I apply this algorithm on the purchase sequences of credit card data?
If so,please also tell me the difference between sequence clustering and association rules on credit card data application. Although I realize that sequence clustering is a fully probabilistic model and it has the capability of prediction, association rules also give the probabilities of purchasing the other products.
Thanks in advance.
To Wong
Hello,
I would really appreciate if you could help me out. I am trying to create a taxonomy to be taken into account into the association rules algorithm. For example, if my data is a group of purchases from a supermarket I could have one client who bought milk, cookies and shampoo, and another who bough cheese, cookies and soap.
I would like to specify that milk and cheese belong to the category "dairy" and shampoo and soap belong to "personal hygene". If there are interesting rules regarding the categories I would like them to be taken into account. Additionally, I would not like to have rules like "milk -> dairy". If one specific object appers in a rule, its corresponding category should not.
In this scenario I could have milk and "personal hygene" in the same rule, but not shampoo and "personal hygene".
I have seen this done by other mining tools but I've been having trouble finding a way to make this possible in Analysis Services.
Thank you very much.
What would be the right design approach for the following problem?
I have a single table called SelectionFactors, which has the following columns and sample data:
ProjectID
Factor
FactorValue
1000
Countries
USA
1000
Countries
Canada
1000
Countries
France
1000
Languages
English
1000
Languages
French
1000
Company Type
Consulting
1000
Company Type
Software
2000
Countries
India
2000
Countries
China
2000
Countries
USA
2000
Languages
English
2000
Languages
Chinese (Simplified)
2000
Languages
Chinese (Traditional)
2000
Languages
Spanish
2000
Company Type
Retail
2000
Company Type
Dairy Products
The problem is to allow a descriptive analysis of the data to find patterns in the users selections. For instance,
if Languages->English is selected, what are the counts of projects for other Factor->Factor Value combinations?
Countries->USA = 2, Countries->Canada=1, Company Type->Consulting=1 and so on.
Since all the data is in this single table, are both the case and nested tables the same? What are the keys and inputs? I only need a descriptive analysis (no prediction) and ALL possible combinations MUST be part of the results; how should the model be designed?
Thank you,
Anna.
MS uses the a priori algorithm in Association Rules, while other DM software have gone to the Novel Algorithm. Can you tell us why MS decided to stay with the a priori? Did you overcome the limitations that it's accused of having? Thanks!
View 5 Replies View RelatedI build a data mining model to predict what are the best studying methods for the student to pass the examinaton.
Create Mining Model StudentAssociation (
Student_No long key,
Gender text discrete predict,
PassOrFail text discrete predict,
StudyMethod table predict ( MethodName text key )
) Using Microsoft_Association_Rules ( Minimum_Support=0.02, Minimum_Probability=0.03 )
The mining table will contain all the methods that the students use, no matter their examination is passed or failed.
The value of PassOrFail will have either 'Pass' or 'Fail'.
According to the above model, can I query the best studying methods?
Or I should only train the model with the student who pass the examination, and ignore all the failed.
Thanks.
Joe.
If I use this code with an association model, it still returns itemsets for me - when it should be returning only nodes with rules associated with them (according to sqlserverdatamining.com). If I try adding 'AND $PROBABILITY > .25' to the where clause, it returns 0 results for every query I try. Any clue why this may be happening?
Code Snippet
SELECT FLATTENED
(SELECT * FROM PredictAssociation([Product],20,
INCLUDE_NODE_ID,INCLUDE_STATISTICS)
WHERE $NODEID<>'')
FROM
[ProductRecommend]
PREDICTION JOIN
OPENQUERY([ds],
'SELECT
[PRODUCTCLASSID],[DESCRIPTION]
FROM
[Product_Table]
WHERE
[PRODUCTCLASSID] = ''1234'' AND [DESCRIPTION] = ''DESC''
') AS t
ON
[ProductRecommend].[Product].[PRODUCTCLASSID] = t.[PRODUCTCLASSID] AND
[ProductRecommend].[Product].[DESCRIPTION] = t.[DESCRIPTION]
This query returns more relevant results than those lacking the filtering by $NODEID, however the results should have higher probabilities than .047! Please help! Thanks!
"If you have a pressing need for this fix, please contact our customer support team."
Yes I have a pressing need for this fix, where I have to contact your customer support team. How do I do that?
You know I only have the evaluation version of SQL Server, but I have to show that this programm is good enough to solve Association Analysis. If I can not show this it wouldn't be bought. Please help me.
TNX
hi
I am using Microsoft association algorithm to find the association between PATIENT CITY ---> likely Disease. I like to know how can i import association model after creating from SQL Server BI studio to use in my ASP.NET web form? such a way when the user enters PATIENT CITY, system prompts associated Disease.
I do have Data mining with SQL Server 2005 book, could't find any resource for my objective.
Please suggest best source or tutorial how can i do
your help and insight is highly appreciated.
Raju
In assotiation rules each rule has a [support, confidence] part. In Microsoft Association Rules there is a [probability,importance] measure in each rule and importance can be greater that 1.
I found the following in msdn but i'm not sure if i understood correctly.
MINIMUM_PROBABILITY: Specifies the minimum probability that a rule is true. For example, setting this value to 0.5 specifies that no rule with less than fifty percent probability is generated.
The default is 0.4.
MAXIMUM_SUPPORT: Specifies the maximum number of cases in which an itemset can have support. If this value is less than 1, the value represents a percentage of the total cases. Values greater than 1 represent the absolute number of cases that can contain the itemset.
The default is 1.
My questions are
1) Can i explain the [probability,importance] in [support,confidence]? If yes, how?
2) What importance>1 means?
Thank you in advance.
Hi, all experts here,
Thanks for your kind attention.
I want to filter the itemsets or rules based on more than 2 attributes, how can we achieve that? (I can only filter them by only one attribute?). Is it possible to achieve that?
Thanks a lot and I am looking forward to hearing from you shortly.
With best regards,
Yours sincerely,
Hi there,
i'm new to this forum .. Maybe my way of expression is not very good, but I hope to be understandable.
I've a sql server 2005 database with 90 columns and more or less 185 thousands records. I've to run microsoft associations rules on my laptop (sony vaio sz3, core 2 duo, 2gb ram).
The problems is that the amount of ram seems not to be enough [it starts to swap when it's reading 240th case)
Because of this, i decided to sample my data by extracting 10thousands records randomnly ... it lasts 25minutes (more or less) now, but it's still to much...
Does a better way exists? What's the problem: column or row numbers?
hope you guys can help me.
i begin for Data mining ( analysis manager - sql server 2000)
i create some mining model with Microsoft_decision_ trees or Clustering. it's oK
but now i want to create a model to know "If customer 1 has product A in their basket, what products should I recommend ".
i read and see that "Microsoft analysis manager sp1" have support association rules.
i install pack 4. but i don't see anything else . how i create a model with association rules.
Hi
I am working on an academic medical project. I have created PATIENT table
PATIENT_ID
NAME |
CITY
DISEASE table
DISEASE_ID
NAME |
and Relationship table[FOREIGN KEYS]PATIENT_DISEASE
PATIENT_ID
DISEASE_ID
I am using Microsoft association algorithm [SQL Server 2005 BI Studio] to find association between PATIENT CITY --> Associated DISEASE. I will be entering dummy data into these tables as this is academic project. I like to know can i be able to find the associated Disease/s with the PATIENT City with this algorithm ? such a way as soon as the user enters PATIENT City, assocaited Disease will be selected from the diseases table? on web interface [asp.net].
i like to know after building this association model, can i use it on my web page to prompt the user associated disease with patient city? or building this model only gives association rules, i need to write a procedure or t-sql statements to implement the association rules?
I am using SQLSERVERDATAMINING.COM tutorials to build the model.
Your information and help is highly appreciated.
regards
I'm looking for suggestions on the right design approach in relation to a problem that resembles Basket analysis. The data to be analyzed is a dimension Attribute_DIM and contains an ID, Attribute and Attribute_Value. Some examples of the data are :
ID Attribute Attribute_Value
1 Color Black
1 Movie Men in Black
1 Book Of Human Bondage
2 Color White
2 Movie Men in Black
2 Book Grapes of Wrath
We need to be able to analyze multiple selections of the dimension. For example,
Men In Black
Grapes Of Wrath Of Human Bondage
Men In Black Black 1 1
White 1 0
I have had some success using the Association Algorithm Mining Model. I think It is an overkill since I only need descriptive and no predictive analysis.
I'm looking for some ideas on the right approach to this problem. Ideally, we need to present the data in a cube and have the possibility to perform member analysis of the dimension.
I have looked at several articles (including http://msdn2.microsoft.com/en-us/library/aa902637(sql.80).aspx and http://www.aspnetpro.net/newsletterarticle/2004/10/asp200410ri_l/asp200410ri_l.asp). I'm not convinced those are the solutions and would appreciate any insight into this problem.
Thank you,
Anna.
Hi,
I've been playing around with the association mining model in SQL server 2005 and built a market-basket analysis of my data that I'm pretty happy with. The next task for me is figuring out how to run DMX queries against the data that I've just mined, so we may possibly use it in a web based application. This wouldn't necessarily be a difficult problem (and still may not be), but every example I've seen for the Mining Model Prediction Designer uses relational databases and I built my mining model off OLAP. Therefore, my predictable attribute is nested and when relating the mining model structure to the relational database that the cube was built off always gives me an error:
"Errors in the high-level relational engine. The 'CompanyName' column could not be found in the top-level clause of the SHAPE statement."
What I would like to do, and I'm not really even sure how I should structure any of my queries, is feed the model a product and have it return a listing of all the products it predicts. Currently, I've only been able to get the designer mode to process a singleton query, and even that didn't return any useful data. I know that this probably can be done pretty easily so any advice you may be able to offer would be greatly appreciated!!
So you may better understand my question, my association mining structure hierarchy looks as this..
[Model] ProductRecommend
[Case][Key]CustomerList
[Case][Attribute]CompanyName
[NestedTable]Product
[Nested][Key]PRODUCTCLASSID
[Nested][Attribute]PRODUCT
With that in mind, I'm trying to perform a query simliar to this:
SELECT
PredictProbability([ProductRecommend].[Product].[PRODUCTCLASSID]), <---- Throws Error for PredictProbability syntax no matter what I try to get to [PRODUCTCLASSID]
(SELECT [PRODUCT] FROM [ProductRecommend].[Product])
From
[ProductRecommend]
NATURAL PREDICTION JOIN
(SELECT 'test' AS [COMPANYNAME],
(SELECT '1234' AS [PRODUCTCLASSID],
'ProductA' AS [PRODUCT]) AS [Product]) AS t
Thanks again for any help!
Hello Everyone. I am a newbie to data mining. I hope that you can help.
I have run the same data mining query against the Decision Tree, Logistical Regession, Neural Network and Assocation Rules mining models. I created seperate tables to contain the results of each of these models. All of the tables have the same structure. The structure is a col#1 with a bigint datatype and col#2 with a numeric(5,5) datatype. All of the models have been successful with outputing the data to their respective tables except the Association Rules model. I am receiving the following error: " Failed to execute data mining query due to the following error: The given value of type SqlDecimal from the data source cannot be converted to type decimal of the specified target column." Is there something special that I need to do with my dmx statement to get the sqldecimal data to insert into the numeric column? What is different about the Association Rules model? I rechecked my dmx statement and it is the same for other models.
Let me know if you need more information.
Thanks
What is the best practice in setting a minimum support threshold for market basket analysis? Is there a formula? Does it depend on ROI you predict?
View 4 Replies View Relatedmanaged plug-in framework that's available for download here: http://www.microsoft.com/downloads/details.aspx?familyid=DF0BA5AA-B4BD-4705-AA0A-B477BA72A9CB&displaylang=en#DMAPI.
This package includes the source code for a sample plug-in algorithm written in C#.
in this source code all .cs files are modified for clustering algorithm
if my plugin algorithm is of association or classification type then what modifications are requried in source code???
Hi, all here,
I am wondering where can I store my mining results in data mining engine? For example, I got mining results like accuracy chart, decision trees, and other formats of results based on different mining algorithms I used for my data mining, so where can I actually store the results for reporting service use later? Is it possible to do that in SQL Server 2005?
Thanks a lot for any help and guidance in advance.
Hi,
I have just run a simple data set through a model to predict a simple true or false value (i.e. binary output)
The Lift Chart/Mining Legend in Analysis Services shows three results €“ Score, Population Correct (%), and Predict Probability (%)
Population Correct I beleive is the percentage of predictions it got right out of the total number of predictions it tried to make. Is this correct?
However, I can€™t work out how the other two are derived in particular the 'SCORE'. To give a live example the scores were as follows:
Model Score Pop Correct Pred Probability
Decision Trees 0.83 76.59% 54.28%
Neural Network 0.75 67.63% 50.05%
Ideal Model 100.00%
Can anyone help with this and give a detailed explanation?
Many thanks,
S Rajput