Questions On Key Column In Case Table And Key Time Column In Nested Table Using Time Series Algorithm
Jun 4, 2007
Hi, all experts here,
Thank you very much for your kind attention.
I am confused on key column of case table and key time column of nested table by using Time Series algorithm.
In my case, the case table structure is as below:
Territory key text (the ID is actually dimrisk_key, in this case, I use the name column binding to combine the Territory column of case table Dimrisks),
While the nested table structure is as below:
Cal_month key time (in this case, actually the ID is dimdate_key, again, I used name column bining property to bind the Cal_month to the ID)
So my question is, as the key column of case table has been set to be Territory, as a result, does the model training still cover all the cases (rows) based on the ID of the table?
Also, in the nested table, as the key time column has been set to Cal_month rather than Dimdate_key of the nested table, as a result, would the single series based on the cal_month?
Hope it is clear for your advices and help.
And I am looking forward to hearing from you shortly.
I want to use time series algorithm to mine data from my case table and nested table. Case table is Date table, while nested table is the fact table. E.g, I want to predict the monthly sales amount for different region (I have region table related to the fact table), how can I achieve this?
Thanks a lot and I hope it is clear for your help and I am looking forward to hearing from you shortly.
I am confused on key time column selection. e.g, I want to predict monthly sales amount, then what column in date dimension should I choose to be the key time column? Is it calendar_date (the key of date dimension) column or calendar_month?
Thanks a lot for your kind advices and help and I am looking forward to hearing from you shortly.
Hello, I was working with Microsoft Time Series (MTS) algorithm and simulated data in order to evaluate/know it a little more. I simulated 24 points of the model y[t] = 5.74-0.1486 y[t-1] + e[t] and 19 points of the model y[t] = 10.48-0.0486 y[t-1] + e[t] (a change of level), where e ~ N(0,0.01). The MTS output is: if time>=23.5 then AR(3) else AR(1): y[t] = 6.23-0.2536 y[t-1]. So, I am wondering: how the algorithm works whit the time variable as a split variable? Like the other variables? Only considering 4 time points? Why the MTS algorithm produces AR(p) models where p is a little large (like the example: I simulated an AR(1) model and the output is an AR(3) model), what about parsimony models? A AR model is a stationary model, so what happen if some data have trend? We need eliminate the trend before the MTS algorithm can be used?Thanks for your time
I just encountered the problem that with Microsoft Time Series algorithm, no more than one case table is allowed? Mining structure is not allowed to contain any nested table?
Or did I miss out anything there? Thank you very much in advance for your kind advices and I am looking forward to hearing from you shortly.
i am trying to associate city in patient table --> disease in diseases table. I want to build association data mining model and use it on web form, such a way when the user enters city associated disease will be displayed.
should i select all 3 table to build the model? could help me to decide what tables should i select as Case and what tables as Nested? what attributes from the table should i select as key, input, predictive ?
i am using data mining tutorials on sqlserverdatamining.com to build this model. is there anything further during my model building i get into confusion? please suggest me where i can find complete resource or inform here.
i appreciate Mr.Jamie for his guidance so far in my academic project. i do have the book 'Data mining with sql server 2005'. I left with just one day to do this and document.
hoping someone could suggest. your help is much appreciated.
Obviosly for Person1 and 200501 I expect to see on MS Time Series Viewer $3000, correct? Instead I see REVENUE(actual) - 200501 VALUE =XXX, Where XXX is absolutly different number.
Also there are negative numbers in forecast area which is not correct form business point Person1 who is tough guy tryed to shoot me. What I am doing wrong. Could you please give me an idea how to extract correct historical and predict information?
I am building data mining models to predict the amount of data storage in GB we will need in the future based on what we have used in the past. I have a table for each device with the amount of storage on that device for each day going back one year. I am using the Time Series algorithm to build these mining models. In many cases, where the storage size does not change abruptly, the model is able to predict several periods forward. However, when there are abrupt changes in storage size (due to factors such as truncating transaction logs on the database ), the mining model will not predict more than two periods. Is there something I can change in terms of the parameters the Time Series Algorithm uses so that it can predict farther forward in time or is this the wrong Algorithm to deal with data patterns that have a saw tooth pattern with a negative linear component.
hi to every one and again i say my question for the first time i thought if i ask my question from this forum i can give my answer exactly but with these answers i see it was just a dream . one person said you can see your answer in book with this title "the datamining with sql 2005 "but i cant find my request and then said you can find in datamning sql2005.com and in this site i cant find a sample about a form that i can show my result of prediftion with time series i dont know how can i earn this code .and a sample about that .please please if every one can answer me ,answer with descripstion about code .i just want codes for connecting between c# and analysis serveice and a description about quality of this code,that means this code, how do it work?
I'm trying to create a DM model using TS algorithm, to predict sales for different products and channels but I can only get it to work using one of those two "dimensions" or columns the other one is ignored (This is, my fact table contains a key for time, a key for channel a key for product and the metrics and the model only seems to allow working with time, the metrics and only one of the other dimensions product or channel ..) Am I missing something?
Again I encountered a very strange problem which displayed the predicted attribute values as percentage format? The data type of the attribute is actually double, why is that?
That's really frustrated.
Thanks a lot in advance for your kind advices and I am looking forward to hearing from you shortly.
First question: How many months of data do you need to make this algorithm to work in Excel 2007? And is there an issue about data types in Excel for this algorithm?
I have found some odd behaviours regarding this. If I use the DM sample Excel 2007 with time series data everything works fine. If I copy and paste data into Excel 2007, from another data source, I can get a forecast of repeating values, that is one value, that will be repeated for each month that I am trying to do a forecast.
Should I avoid having time members for forecast dates in a column? Sometimes my forecast values will be placed below my dates that do not have values. If I am forecasting months in 2008, with month values from 2007 and 2006 the forecast values will be placed below my 2008 empty months.
I encountered a very strange problem again. Why the time series displayed on the chart are so strange? The Key time column I chose for my time series algorithm is cal_month(e.g 199001...), but why the date displayed on the time series chart is like :05/06/2448? (it should be like 199001..?) What is that data? And where exactly did it come from? What is the exact cause of this?
Hope it is clear for your help.
I am really confused on this and thanks a lot for your kind advices and help and I am looking forward to hearing from you shortly.
Hi all, I have two tables (staging and Cdate) and neither objects has any constraints. staging table has ID, date, A, B, and C fields and Cdate has id,date and day fields. I need to update/insert date from Vdate into staging where staging ID=' ' and date is null Here is the code I wrote, however, it seemed the information was updated to one date only instead of time series - Cdate contains time series in column date. Anyone can help to fix it? Thank you for the help!
update s set s.date=c.date FROM cdate c join staging s on(s.id=c.id) Where s.date is null and id=2
i have a time series table which generates a flag for every 10 mins. the table looks as below. I am trying to write a sql query which gives me the start date and end date of a particular flag, each time the flag starts. i tried to do it using cursors and actually joining the table to itself based on a 10 min offset but couldn't get the required results.
With Sql Server Management Studio, while creating/modifying a table I want to specify one of its columns to store values in lower case only. Can it be done through the designer or by some other means?
I have a very simple time series model which processing works fine without any problem. However when I run the following query
SELECT
[TimeSeries].[PriceChange],
[TimeSeries].[Symbol],
PredictTimeSeries(PriceChange, -3, 2)
From
[TimeSeries]
WHERE
[TimeSeries].[Symbol] = 'x'
I get the following error:
TITLE: Microsoft SQL Server 2005 Analysis Services ------------------------------ Error (Data mining): A time series prediction was requested with a start time further in the past than the internal models of the mining model, TimeSeries, specified in the HISTORIC_MODEL_GAP and HISTORIC_MODEL_COUNT parameters can process.
The following is the excerpt of the minding model script related to the two parameters:
<AlgorithmParameters>
<AlgorithmParameter>
<Name>MISSING_VALUE_SUBSTITUTION</Name>
<Value xsi:type="xsdtring">Previous</Value>
</AlgorithmParameter>
<AlgorithmParameter>
<Name>HISTORIC_MODEL_GAP</Name>
<Value xsi:type="xsd:int">1</Value>
</AlgorithmParameter>
<AlgorithmParameter>
<Name>HISTORIC_MODEL_COUNT</Name>
<Value xsi:type="xsd:int">10</Value>
</AlgorithmParameter>
</AlgorithmParameters>
These HISTORIC_MODEL_GAP (1) and HISTORIC_MODEL_COUNT (10) should accommodate PredictTimeSeries(PriceChange, -3, 2). Could anyone shed some light on this?
I was working with Microsoft Time Series model (MTS) with some data, when in the mining model viewer, decision tree tab, I realized that the key time variable that I define, it was acting like a split variable.
So, I ask you, this is possible?, because, for me, this should not happen€¦.
After, I review the Data Mining Tutorial by Seth Paul, Jamie MacLennan, Zhaohui Tang and Scott Oveson, and I found, in the Forecasting part, that the key time variable (Time Index) it was acting like a split variable too, in for example, M200 pacific:Quantity and R250 Europe:Quantity.
So people, it€™s possible that a key time variable act like a split variable in a MTS model?
I have an SSIS package that moves data from SQL Server to an legacy Access database. In SQL Server, there is a date/time column that I need to split into a separate date column and time column in the access database. Initially I just created a derrived column for the time and set the expression equal to the source date/time column from SQL Server. Unfortunately, that just makes the date column and time column the same having the full date/time.
What expression can I use during a derrived column transformation to assign just the date to a derrived column and just the time to another derrived column?
I have MS Time Seeries model using a database of over a thousand products each of which has hundreds of cases. It amazingly takes only a few minutes to finish processing the model, but when I click Mining Model Viewer to view the models, it takes many hours to show up. Once the window is open, I can choose model for different products almost instantly. Is this normal?
I am trying to create a new mining structure with case table and nested table, the case table (fact table) has alread defined the relationships with the nested table(dimension table), and I can see their relationship from the data source view. But why the wizard for creating the new mining structure showed that message? Why is that? And what could I try to fix it?
Hope it is clear for your help.
Thanks a lot for your kind advices and I am looking forward to hearing from you shortly.
How can I obtain just the time portion from a date/time column? My data contains "2008-05-19 09:30:00.000" Actually, all I want/need is the hh:mm part of it.
I need to take a temporary table that has various times stored in a text field (4:30 pm, 11:00 am, 5:30 pm, etc.), convert it to miltary time then cast it as an integer with an update statement kind of like:
Update myTable set MovieTime = REPLACE(CONVERT(CHAR(5),GETDATE(),108), ':', '')
how this can be done while my temp table is in session?
As we are allowed to select one table as both case table and nested table, however what is the benefit of using one table as both case table and nested table? Thanks in advance for your advices.
I have two columns in a table:StartDate DateTime and StartTime DateTime.The StartDate column holds a value such as 07/16/2004The StartTime column holds a value such as 3:00:00 PMI want to be able to add them in a stored procedure.When I use StartDate + StartTime I get a date two days earlier than expected.For example, instead of 7/16/2004 3:00:00 PM StartDate + StartTime returns7/14/2004 3:00:00 PM.Can anyone point out wht I'm doing wrong with this one?Thanks,lq
For example,I have a table "authors" with a column "author_name",and it has three value "Anne Ringer,Ann Dull,Johnson White".Here I want to create a new table by using a select sentence,its columns come from the values of the column "author_name".
can you tell me how can I complete this with the SQL?
I am a bit confused for the model evaluation (lift chart), should we map all the columns for both the mining structure and the case table? I mean for those predictive models, we have a predict column, shouldnt we ignore the mapping of the predictive column between the mining structure and the case table? But it seemes we are not allowed to miss the predictive column mapping between the mining structure and the case table.
Why is that? Could any experts here give me some explanation on that?
Hope my question is clear for your help.
Thanks a lot and I am looking forward to hearing from you shortly.
I am trying to select patient table as case and diseases table as nested to create an association model. i m getting following error.
Disease table cannot be used as a nested table because it does not have a many-to-one relationship with the case table. You need to create a many-to-one relationship between the two tables in the data source file.
i have created a relationship by dragging Disease_id from diseases table on Patient_id in patient table. when i am trying to select Patient_id as key, City as input, it is not showing disease_id to choose as a predict column.
please suggest me if i am doing anything wrong? i have not done any thing to do my datbase, just selected the tables i want to create an association model on and trying to create association model.
