Error Not Enough Space For Temporal Database When Processing Decision Tree Model
Sep 4, 2007
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.
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Jan 9, 2008
Hi,
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."
Does anyone have a clue of how can I solve it?
Thank you.
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May 18, 2007
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?
Thanks in advance.
Nick
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Feb 19, 2007
Hi
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.
Thanks,
Nathan
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Sep 15, 2006
Hi,
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.
Regards,
Bernaridho
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Jan 5, 2007
Hi,
I am trying to run one of the mining models from the book "Delivering BI using SQl Server 2005" but I am running into "Decision Trees found no splits for model". The mining structure has 4 columns, the fourth one being marked as "Predict Only". My Cube slice for the model has sufficient data in the cube. I am lost.. Help!!
Regards
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Apr 16, 2007
I'm having this problem.....
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.......
Thank you again.........
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Jun 28, 2007
Hi,
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?
Thanks a lot!
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Oct 20, 2007
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.
Any tip?
Thanks,
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May 2, 2006
I have an example case below :
Customer Id
Debt Level
Income Level
Employment Type
Credit Risk
1
High
High
Self-Employed
Bad
2
High
High
Salaried
Bad
3
High
Low
Salaried
Bad
4
Low
Low
Salaried
Good
5
Low
Low
Self-Emplyed
Bad
6
Low
High
Self-Employed
Good
7
Low
High
Salaried
Good
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.
Thanks a lot.
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May 16, 2006
Hi again ....i'm trying to understand the works of microsoft decision tree algorithm
I have an example case below :
Customer Id
Debt Level
Income Level
Employment Type
Credit Risk
1
High
High
Self-Employed
Bad
2
High
High
Salaried
Bad
3
High
Low
Salaried
Bad
4
Low
Low
Salaried
Good
5
Low
Low
Self-Emplyed
Bad
6
Low
High
Self-Employed
Good
7
Low
High
Salaried
Good
My question is how about the equations used to determine a split?
Please explain me detailed.
Thanks a lot.
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Dec 5, 2007
Hello,
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.
Regards
Anurag
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Apr 12, 2006
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).
thanks for anyone help
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Jun 10, 2006
hai ...............all
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.
thank you so much
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Dec 6, 2007
Hi all,
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.
Thank you in advance
Manolis
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Feb 15, 2008
In the previous thread I said when I want to create a model and structure, in process time one error appeared that I said.
Now I think this error is because of my structure now I€˜ve one request i send my project and please see that and say what is this error?
Thanks a lot.
For creating mining structure and mining model I use the code of chapter14 file that one person had put for me
Please run this project and then say whay when I process my model ,the process do incorrectly.
in this code button 1 is for showing the anme of data bsase and table and column of that in currenyt server and then with button 2 i want ot creat model and struture and data source data source view
now please run this code and then say whay i have error for process model .
please run and answer me
thanks a lot
string last;
int ts;
string[] items;
string ky;
string t;
string dbnam;
string tblnam;
public Form1()
{
InitializeComponent();
}
private void button1_Click(object sender, EventArgs e)
{
SqlConnection con = new SqlConnection("Data Source=localhost;Integrated Security=True");
con.Open();
SqlCommand cmd1 = new SqlCommand(" EXEC sp_databases;", con);
DataSet ds = new DataSet();
SqlDataAdapter da1 = new SqlDataAdapter();
da1.SelectCommand = cmd1;
da1.Fill(ds, "1");
this.comboBox1.DisplayMember = "database_name";
this.comboBox1.ValueMember = "database_name";
this.comboBox1.DataSource = ds.Tables["1"];
SqlCommand cmd2 = new SqlCommand("USE " + comboBox1.Text.ToString() + " EXEC sp_tables @table_owner ='dbo';", con);
SqlDataAdapter da2 = new SqlDataAdapter();
da2.SelectCommand = cmd2;
da2.Fill(ds, "2");
this.comboBox2.DisplayMember = "table_name";
this.comboBox2.ValueMember = "table_name";
this.comboBox2.DataSource = ds.Tables["2"];
SqlCommand cmd3 = new SqlCommand("USE " + comboBox1.Text.ToString() + " EXEC sp_columns @table_name = N'" + comboBox2.Text.ToString() + "', @table_owner = N'DBO';", con);
SqlDataAdapter da3 = new SqlDataAdapter();
da3.SelectCommand = cmd3;
da3.Fill(ds, "3");
DataTable dt = new DataTable();
dt.Columns.Add("column_name");
dt.Columns.Add("data_type");
for (int i = 0; i < ds.Tables["3"].Rows.Count; i++)
{
DataRow dr = ds.Tables["3"].Rows;
dt.Rows.Add(dr[3], dr[5]);
}
con.Close();
dataGridView1.Columns.Clear();
dataGridView1.DataSource = dt;
DataGridViewCheckBoxColumn DVCC = new DataGridViewCheckBoxColumn();
DVCC.Name = "key";
dataGridView1.Columns.Add(DVCC);
DataGridViewCheckBoxColumn DVCC2 = new DataGridViewCheckBoxColumn();
DVCC2.Name = "input";
dataGridView1.Columns.Add(DVCC2);
DataGridViewCheckBoxColumn DVCC3 = new DataGridViewCheckBoxColumn();
DVCC3.Name = "predict";
dataGridView1.Columns.Add(DVCC3);
}
private void Form1_Load(object sender, EventArgs e)
{
}
private void button2_Click(object sender, EventArgs e)
{
dbnam = comboBox1.Text;
tblnam = comboBox2.Text;
Microsoft.AnalysisServices.Server srv = new Server();
srv.Connect("data source=localhost");
string dbname;
dbname = comboBox1.Text;
Database dbNew = new Database(dbname,
Utils.GetSyntacticallyValidID(dbname, typeof(Database)));
srv.Databases.Add(dbNew);
dbNew.Update();
//***************************//
string DataSourcename;
DataSourcename = comboBox1.Text;
RelationalDataSource dsNew = new RelationalDataSource(
DataSourcename,
Utils.GetSyntacticallyValidID(
DataSourcename,
typeof(RelationalDataSource)));
dsNew.ConnectionString = "Provider=SQLNCLI;Data Source=localhost;" +
"Initial Catalog="+comboBox1.Text+";Integrated Security=SSPI"; ;
dbNew.DataSources.Add(dsNew);
dsNew.Update();
//**************************//
DataSet dset = new DataSet();
SqlConnection cn = new SqlConnection("Data Source=localhost;" +
"Initial Catalog="+comboBox1.Text+";Integrated Security=true");
SqlDataAdapter da = new SqlDataAdapter("select * from "+comboBox2.Text,cn);
da.FillSchema(dset, SchemaType.Mapped, comboBox2.Text);
DataSourceView dsv = new DataSourceView(comboBox1.Text, comboBox1.Text);
dsv.DataSourceID = comboBox1.Text ;
dsv.Schema = dset.Clone();
dbNew.DataSourceViews.Add(dsv);
dbNew.Update(UpdateOptions.ExpandFull);
MiningStructure ms = dbNew.MiningStructures.Add(comboBox2.Text, Utils.GetSyntacticallyValidID(comboBox2.Text,
typeof(MiningStructure)));
ms.Source = new DataSourceViewBinding(comboBox1.Text);
ms.CaseTableName = comboBox2.Text;
int count = dataGridView1.Rows.Count;
for (int i = 0; i < count - 1; i++)
{
if (Convert.ToBoolean(dataGridView1.Rows.Cells["key"].Value) | Convert.ToBoolean(dataGridView1.Rows.Cells["input"].Value) | Convert.ToBoolean(dataGridView1.Rows.Cells["predict"].Value))
{
string X;
X = Convert.ToString(dataGridView1[0, i].Value);
ScalarMiningStructureColumn I;
I = new ScalarMiningStructureColumn(X,
Utils.GetSyntacticallyValidID(X, typeof(ScalarMiningStructureColumn)));
if (!Convert.ToBoolean(dataGridView1[2, i].Value))
{
I.IsKey = false;
I.Type = conv(Convert.ToString(dataGridView1[1, i].Value));
I.Content = "Continuous";
}
else
{
ky = X;
I.IsKey = true;
I.Content = "Key";
I.KeyColumns.Add(comboBox2.Text, X, OleDbType.Integer);
}
ms.Columns.Add(I);
}
// //****************************************************************************************************************************************//
}
ms.Update();
MiningModel mm = ms.MiningModels.Add(comboBox2.Text,
Utils.GetSyntacticallyValidID(comboBox2.Text, typeof(MiningModel)));
mm.Algorithm = "Microsoft_Time_Series";
for (int i = 0; i < count - 1; i++)
{
if (Convert.ToBoolean(dataGridView1.Rows.Cells["key"].Value) | Convert.ToBoolean(dataGridView1.Rows.Cells["input"].Value) | Convert.ToBoolean(dataGridView1.Rows.Cells["predict"].Value))
{
string X;
X = Convert.ToString(dataGridView1[0, i].Value);
MiningModelColumn mc = new MiningModelColumn(X,
Utils.GetSyntacticallyValidID(X, typeof(MiningModelColumn)));
mc.SourceColumnID = ms.Columns[X].ID;
if (Convert.ToBoolean(dataGridView1[2, i].Value))
mc.Usage = "Key";
else
if ((Convert.ToBoolean(dataGridView1[3, i].Value)) && (Convert.ToBoolean(dataGridView1[4, i].Value)))
mc.Usage = "Predict";
else
mc.Usage = "PredictOnly";
mm.Columns.Add(mc);
}
}
mm.Update();
ms.Process(ProcessType.ProcessStructure);
mm.Process(ProcessType.ProcessDefault);
srv.Disconnect();
SqlDataAdapter da2 = new SqlDataAdapter("select " + ky + " from " + comboBox2.Text, cn);
DataTable dt=new DataTable();
da2.Fill(dt);
ts = dt.Rows.Count;
items = new string[ts+10];
for (int i = 0; i < ts; i++)
{DataRow dr = dt.Rows;
items=dr[0].ToString();
}
last = items[ts-1];
}
private void comboBox1_SelectedIndexChanged(object sender, EventArgs e)
{
SqlConnection con = new SqlConnection("Data Source=localhost;Integrated Security=True");
SqlCommand cmd2 = new SqlCommand("USE " + comboBox1.Text.ToString() + " EXEC sp_tables @table_owner ='dbo';", con);
con.Open();
SqlDataAdapter da2 = new SqlDataAdapter();
da2.SelectCommand = cmd2;
DataSet ds = new DataSet();
da2.Fill(ds, "2");
con.Close();
this.comboBox2.DisplayMember = "table_name";
this.comboBox2.ValueMember = "table_name";
this.comboBox2.DataSource = ds.Tables["2"];
if (comboBox2.Items.Count > 0)
{
comboBox2.SelectedIndex = 0;
}
}
private void comboBox2_SelectedIndexChanged(object sender, EventArgs e)
{
SqlConnection con = new SqlConnection("Data Source=localhost;Integrated Security=True");
SqlCommand cmd3 = new SqlCommand("USE " + comboBox1.Text.ToString() + " EXEC sp_columns @table_name = N'" + comboBox2.Text.ToString() + "', @table_owner = N'DBO';", con);
con.Open();
SqlDataAdapter da3 = new SqlDataAdapter();
da3.SelectCommand = cmd3;
DataSet ds = new DataSet();
da3.Fill(ds,"3");
con.Close();
dataGridView1.DataSource = "empty";
con.Close();
DataTable dt = new DataTable();
dt.Columns.Add("column_name");
dt.Columns.Add("data_type");
for (int i = 0; i < ds.Tables["3"].Rows.Count; i++)
{
DataRow dr = ds.Tables["3"].Rows;
dt.Rows.Add(dr[3], dr[5]);
}
dataGridView1.Columns.Clear();
dataGridView1.DataSource = dt;
DataGridViewCheckBoxColumn DVCC = new DataGridViewCheckBoxColumn();
DVCC.Name = "key";
dataGridView1.Columns.Add(DVCC);
DataGridViewCheckBoxColumn DVCC2 = new DataGridViewCheckBoxColumn();
DVCC2.Name = "input";
dataGridView1.Columns.Add(DVCC2);
DataGridViewCheckBoxColumn DVCC3 = new DataGridViewCheckBoxColumn();
DVCC3.Name = "predict";
dataGridView1.Columns.Add(DVCC3);
}
public string conv(string data_type)
{
if (data_type == "int" | data_type == "tinyint" | data_type == "smallint" | data_type == "bigint")
t = "Long";
else
if (data_type == "char" | data_type == "nchar" | data_type == "varchar" | data_type == "nvarchar" | data_type == "binary" | data_type == "varbinary" | data_type == "image" | data_type == "text" | data_type == "ntext" | data_type == "timestamp" | data_type == "uniqueidentifier")
t = "text";
else
if (data_type == "decimal" | data_type == "float" | data_type == "money" | data_type == "smallmoney" | data_type == "numeric" | data_type == "real")
t = "Double";
else
if (data_type == "datetime" | data_type == "smalldatetime")
t = "Date";
else
if(data_type=="bit")
t="Boolean";
return t;
}
}
}
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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.
Thanks
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Aug 24, 2007
Dear All,
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?
Thanks
Tony Chun Tung Siu
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May 2, 2007
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:
- CaseTable.CaseID
- MiningModel.OutputAttribute
- PredictProbability(MiningModel.OutputAttribute)
- PredictNodeId(MiningModel.OutputAttribute)
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?
Thanks in advance for any information or advice.
- Paul
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Aug 24, 2007
Dear All,
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?
Thanks and regards
Tony Chun Tung Siu
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Feb 8, 2007
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
------------------------------
ADDITIONAL INFORMATION:
Query (1, 6) The '[System].[Microsoft].[AnalysisServices].[System].[DataMining].[DecisionTrees].[GetTreeScores]' function does not exist. (Microsoft OLE DB Provider for Analysis Services 2005)
------------------------------
BUTTONS:
OK
------------------------------
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Nov 26, 2007
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?
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Nov 4, 2015
I get the following error while processing a SSAS tabular model (2014) on a new server.The SSAS service on this server is running under a login which has access to the SQL server data sources. I tried changing the provider to OLEDB from SQLCLNI11 in the connection string but that doesn't work too. The error message isn't useful to debug further.
The cube processing succeeds on a different server. I scripted out the cube DB and ran it on the new server and am trying to process full but it fails with the following error.
Error Message:
The operation failed because the source database does not exist, the source table does not exist, or because you do not have access to the data source.
More Details:
OLE DB or ODBC error: A network-related or instance-specific error has occurred while establishing a connection to SQL Server. Server is not found or not accessible. Check if instance name is correct and if SQL Server is configured to allow remote connections.
For more information see SQL Server Books Online.; 08001; SSL Provider: No credentials are available in the security package
; 08001; Client unable to establish connection; 08001; Encryption not supported on the client.; 08001.
A connection could not be made to the data source with the DataSourceID of 'd7a37dae-be87-44e0-a8b2-498069af82c9', Name of 'connection name'.
An error occurred while processing the partition 'XXXX_460f3467-1a99-4dc9-aaf2-bcf3d54a5c4c' in table 'XXXX_460f3467-1a99-4dc9-aaf2-bcf3d54a5c4c'.
The current operation was cancelled because another operation in the transaction failed. The operation failed because the source database does not exist, the source table does not exist, or because you do not have access to the data source.
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Sep 22, 2006
Hi,
is there a way to import a decision tree-model from pmml where a node contains two or more states of an attribute as the split-rule?
Example:
...
<Node recordCount="600">
<CompoundPredicate booleanOperator="or">
<SimplePredicate field="color" operator="equal" value="red" />
<SimplePredicate field="color" operator="equal" value="green" />
</CompoundPredicate>
<ScoreDistribution value="true" recordCount="200"/>
<ScoreDistribution value="false" recordCount="400"/>
</Node>
...
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.
How can i import such a node in SqlServer 2005?
Thank you in advance for any help
Chris
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Dec 7, 2006
Hi,
I am using MS Decision Trees algorithm and for a specific model i get the above warning.As a result of that i dont get any splits in my tree. Is there anything i can do to avoid this?
Thank you for reading
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Aug 4, 2015
How to fix this SQL error event logg 17204 and 17207 ?
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Jul 20, 2005
hello i have implemented joe celko's model to store heirarchy and itworks well and nicei have a question about SQLthis is the actual tablemember side left right------------------------------------------nancy L 1 36andrew L 4 21steven R 5 12ina L 6 7david R 10 11margaret L 13 20ann R 14 15laura L 18 19janet R 24 35michael L 25 30dan R 26 27ron L 28 29robert R 33 34the Side column is to tell its left, or right. this is a binaryheirarcy.i have this problem i have to solve, im still banging my head. Ifgiven the member'Nancy' , i need to find left-most(Laura) and right-most(Robert)'Janet' = left most is ron, right most is robert'Andrew = left most is laura, right most is DavidHope u get my plan. could u help me with the sql ?
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Oct 21, 2007
I have two questions about the regression tree of Microsoft Decision Trees algorithm.
1. The mining legend window has a column named Histogram showing a bar for each coefficient. What does this bar mean?
2. Since each node of a regression tree corresponds to a linear regression, how can I find the regression coefficient of each node? I mean the coefficient that tells how good the regression is.
Any tip will be greatly appreciated.
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Jun 15, 2007
Can I ask how to split the dataset into training and validation when running descision tree model?
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Oct 18, 2012
how can i automatically update my tabular model in the future when there's an update in my database.
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Dec 18, 2007
I am using Sequence Clustering algorithm. (I've built several models with Clustering algorithm and Decision Trees for this client, which work fine.).
Background: Sequence data must be stored in a nested table, which can have only 1 non-key attribute.
I specify a mining model structure with the nested table key as the datetime, and the nested table discrete prediction column as [sort name] . this builds the model fine.
When I try to process this data mining model, I get Process failed: "Errors in the OLAP storage engine: The sort order specified for distinct count records is incorrect".
Iit may be that OLAP distinct count requests numerical data type, but not from the examples I've seen. Tried this anyway €“ doesn€™t work on numeric either €“ same problem.
Any Suggestions?
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Jul 9, 2007
I have transferred a database from SQL 2000 to SQL 2005 and now I am getting an error when I try to run backup. I get there error "An error occurred while processing 'BackupMetadata' metedata for datase ID..." Does anyone have any suggestions on how to resolve this error?
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Dec 4, 2007
Last week we reset the Model datable to autogrow. Now I get an error when I try to go into it. (I discovered this since I can no longer go into the interface of the program). I wasn't here when the changes were made to the Database Model, but the change was made because the transaction log was filled up.
Help.. I'm such a newbie.
anke
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