I need bank database for graduate thesis.I use database make FRAUD DETECTION IN A FINANCE ASSOCIATION BY DATA MINING.

I'd be happy to help.pleaseee

friends i hav taken up a project in which i need to implement naive bayes classifier in java to classify a mobile sms as spam or non-spam based on its textual content..i am beginner in data mining so i am not yet adept to implement it...      pls help me.

my id is : nik_icy@yahoo.co.in     

pls mail it to above id or atleast give me some links where i can find them....

thanks in advance :-)

Hi friends,

I need a source code of classification algorithms K-NN, decision tree, neural network, SVM. those algorithms i want to classify to a test data. please help me its urgent.

I want to develop a .net application which anonymizes data. the concept i need to use is multirelational k-anonymization. I want to know what is clustering based anonymization and why LM metric is needed in that? what is LM metric basically ? document says it is a costmetric. want help regarding these concepts.

Hi all,

I'm stucked in a little problem, I hope you can help me. I'm using Clementine 10.1

What I want to do is to export some information from a Regresion Model by a script, for instance the R-squared of the model.

It is possible to use "export model model_name summary as path_name.html format html" to export a summary of the model, but there is just information about the Betas, nothing else.

However, without using scripts, from the interface of the model, in the advance tab, you can click on -> export HTML -> advance, so you can export the R-squared and more important information about the model, what I would like to do is export this from script. How can I do it?

If it is not possible to export this information, is there any way to acces it? a table or a specific file?

Thanks you very much.

Hello All,

I'm working on a project of data mining using medical data sets.

the objective is to build a data mining model that predict the survivability of cancer patients based on the medical record.

I decided to use decision tree algorithm to build the model.

I'm using Oracle database 11g and oracle data miner (ODM).

My question is about the accuracy of the model. The results shows that the model correctly predict 97% of the patients as a survival but the prediction of the unsurvivable is quite low (under 40%). 

So my question is about the results. Is this result make any sense, is it possible that a classification model correctly predict only one of the classes? When I used the same data set on Naive Bayes algorithm it correctly predict both of the classes around 78%.

I'm really confused about these results. is it possible that 2 classification algorithms give these different results.

I really appreciate any help or hints.

Hi!

I have been assigend a bad first assignment. I have a data that has more than 100 columns and 1800 rows. There are blanks and values or symbols unknow. I have no clear idea about the column names as well. I need to use ID3. Now I guess I have to prepare the data first. How to reduce the number of columns? Do I need to study clsaafier, reduct, feature selection - algorithms? If yes could you please list the main algorithms in tis category. And I also don't kno how to make a tree? Vista does not support graphic mode, so how can I draw a decision tree in C++?

 I have learnt to calculate Entropy only by now that too for a 10 record sample data. I read a paper "Implementation of ID3 - Decision Tree Algorithm" by Sharad Verma and Nikita Jha. I don't even know if I am on the right track.

 In need of your help,

Nidhi

India

Hi i'm new to clementine, i need to randomly split a database of 4000 records into 2 files, each with 2000 records.

Please advice how can i split the database randomly

Thank you

Estelle

Extended paper deadline: MARCH 7, 2010, 23:59:59 PDT

** Accepted papers will be published in the proceedings by Springer LNCS/LNAI **
** Format can be Springer LNAI with up to 12 pages**
** Papers should be submitted through the BI2010 submission system:
http://www.easychair.org/conferences/?conf=bi2010 **


=====================================
Call For Papers
The International Workshop on Behavior Informatics (BI2010)
June 20, 2010 Hyderabad, India
http://bi2010.behaviorinformatics.org/

Held in conjunction with
The 14th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD2010)
http://www.iiit.ac.in/pakdd2010/

Important dates:
*   Electronic submission of full papers:   MARCH 7, 2010
*   Notification of paper acceptance:       March 20, 2010
*   Camera-ready copies of accepted papers: March 30, 2010
*   BI2010 workshop date:                   June 21, 2010


=====================================
Call for papers to Special Sessions with PAKDD-BI2010
"   Behavior Representation and Modeling
    Submissions on fundamentals for modeling behaviors, behavior networks, group behaviors, behavior interactions, as well as behavioral impacts, trust, reputation, risk, etc.
"   Multi-object/agent Behavior Analysis
    Submissions on data mining and machine learning for analyzing behaviors in multi-agents, multi-objects, including interaction linkage etc.
"   Social Interaction Analysis
   Submissions on analyzing interactions occurring in social networks, internet, blogs, communities, government-customer interactions, etc.
"   Group Behavior Pattern Mining
    Submissions on data mining and machine learning for patterns in group behaviors, community interactions, multi-source and multi-entity interactions, etc.

=====================================
Call for papers to general sessions

Topics: Contributions on the following and other related topics are solicited:
*   (1) Foundations for BI
    · Formal methods
    · Temporal logic
    · Model checking
    · Statistic relational learning
    · Advanced Bayesian network
    · Multiagent systems
    · Self-organization systems
    · Adaptive systems
    · Complex sequence analysis
    · Temporal-sequential pattern mining
    · Impact-oriented behavior mining
    · Event/activity/action mining
    · Agent-based data mining
    · Frequent pattern mining
    · Domain-driven behavior mining
    · Behavior data visualization
*   (2) Behavior Modeling and Representation
    · Abstract behavior model
    · Behavior life cycles
    · Behavior structure understanding
    · Behavior detection and extraction
    · Sequential behavior modeling
    · Parallel/concurrent behavior modeling
    · Distributed behavior modeling
    · Behavior dynamics
    · Temporal-spatial relationship modeling
    · Behavior privacy processing
*   (3) Behavior Pattern Analysis
    · Frequent behavior pattern
    · Behavior classification
    · Behavior clustering
    · Demographic-behavioral combined pattern
    · Interaction pattern analysis
    · Stream behavior pattern
    · Coupled behavior pattern
    · Evolutionary behavior pattern
    · Incremental behavior pattern
    · Combined behavior pattern
*   (4) Behavior Impact Analysis
    · Positive/negative impact modeling
    · Risk, benefit, cost and trust of behavior
    · High-impact behavior identification
    · Impact-transferred behavior pattern
    · Cause-effect analysis
    · Exceptional/outlier behavior
    · Critical event detection and prediction
    · Behavior reputation and trust
    · Behavior security, risk, and privacy
    · Personalized behavior
*   (5) Behavior Emergence
    · Behavior self-organization
    · Behavior evolution
    · Behavior impact formation and evolution
    · Behavior group emergence
    · Behavior mobility
    · Behavior-environment interaction
    · Influence formation and evolution
    · Group behavior formation and evolution
    · Trend, burst, opinion and event formation and evolution
*   (6) Behavior Network
    · Intrinsic mechanisms inside a network
    · Behavior network topological structures
    · Convergence and divergence of associated behavior
    · Hidden group and community formation and identification
    · Linkage formation and identification
    · Community behavior analysis
*   (7) Behavior Simulation
    · Behavior convergence and divergence process
    · Behavior learning and adaptation
    · Group behavior formation and evolution
    · Behavior interaction and linkage
    · Behavior impact formation
    · Behavior effect, impact and influence process
    · Critical event replay
    · Situated behavior interaction
    · Organizational/social factor impact process
*   (8) Behavior Presentation
    · Rule-based behavior presentation
    · Flow visualization
    · Tree-based behavior representation
    · Graph-based behavior modeling and presentation
    · Sequence presentation and visualization
    · Dynamic/hidden group presentation
    · Dynamic/realtime behavior presentation
    · Visual behavior network
*   (9) Behavior Evaluation Mechanisms
    · Behavior impact metrics
    · Behavior risk metrics
    · Behavior effect/influence metrics
    · Behavior pattern significance
    · Behavior pattern actionability
*   (10) Behavior Use and Management
    · Behavior compliance
    · Multi-agent behavior analysis
    · Web usage mining
    · Customer analytics
    · Consumer analytics
    · Recommender system
    · Personalized analysis
    · Fraud detection
    · Misuse and anomaly detection
    · Human-computer interactions
    · AI games
    · Facial expression and human gesture analysis
    · Computational linguistics
    · Intelligent decision support system
    · Student learning behaviors in intelligent tutoring system
    · Criminal behavior analysis
    · Organizational behavior analysis
    · System behavior analysis
    · Social networking behavior analysis
    · Behavior analysis in video data
    · Enterprise process and workflow analysis

=====================================
About Behavior Informatics 2010

Objective: BI2010 provides a premier forum for sharing research and engineering results,
    as well as potential challenges and prospects encountered in Behavior Informatics, namely towards
        deep and quantitative representation, modeling, analysis, mining, presentation, management and applications
        of behavioral data, composed of behaviors, behavior subjects and objects, behavior networks, organizational
        behavior, social behavior, system behavior, group behavior, behavior evolution, causes and effects, and/or behavior impacts.

Scope: The BI2010 workshop welcomes theoretical work and applied disseminations aiming to:
*   Behavior modeling and representation: formalizing behaviors, relationships, impact and networks.
*   Behavior analysis and mining: behaviors associated with high impacts are of particular importance,
        while impact-oriented behaviors are often sparse, rare and imbalanced isolated in business and data;
    analyse impact-oriented behavior patterns involves different pattern types and computational challenges.
*   Analysis of behavior social networks: handling challenging issues such as convergence and divergence of behaviors,
    and the evolution and emergence of hidden groups and communities.
*   Extracting discriminative behavior patterns from high-dimensional, high-frequency,
    high-density, and huge amount of data.
*   Large intra-class variance between behaviors: Due to the highly overlapped nature of behavior data,
    it is extremely difficult to build a robust behavior model which is tolerant for one behavior category
    while differentiate amongst other categories.
*   Behavior data processing from transactional space to behavior feature space.
   
Post-workshop publication:
*   A special Issue on Behavior Modeling, Analysis and Mining is under planning (to be confirmed).

General Co-Chair:
*   Philip S Yu
    University of Illinois at Chicago USA
   
Co-Chairs:
*   Longbing Cao, University of Technology Sydney, Australia
*   Jaideep Srivastava, University of Minnesota, USA
*   Graham Williams, Australian Taxation Office, Australia
*   Hiroshi Motoda, Osaka University and AFOSR/AOARD, Japan 

Supported by
Behavior Informatics - Special Interest Group (BI-SIG)
http://www.behaviorinformatics.org

Contact: 
Email: bi2010@behaviorinformatics.org
 

Hello

 I was wondering if someone could give me some advice. I have just started a module of data mining. I have been told to collect a dataset and have now been asked to construct a data mining project on this.

 The dataset i have obtained is 6 years of customer data on rebates. I am just wondering would you have any suggestions in terms of data mining what i could do with this dataset? what would be the best algorithms to apply to this.

 I would appreciate any suggestions or advice.

Hi..!

i need source code for making simple machine learning c4.5 decision tree in PHP, with training and testing implementation with new dataset.

please, just send it to my e-mail : randymaghaz@gmail.com

It would be great if you help me!

thanks

i need to know about the application of graph mining

                                   thanks 

Hello

I´m new to Clementine, so my question may sound a little "strange" (hope it´s an easy one for you guys).

For my data sources as well as my outputs I would like to keep the filenames/pathnames "dynamic".

So one month my input is for example \\path\200912\inputfile200912.xls next month it´s \\path\201001\inputfile201001.xls   ... same goes for the outputs.

What I was planning to do was create a "Master.xls" which contains the current pathnames. In a script I want to read this xls and set variables for the pathnames, then continue with the execution of the streams.

Any ideas how to do this ?? and how to assign the dynamic Filename (inputfile"200912" and "inputfile"201001)

Thx a lot, and greetinx

Markus (Vienna, Austria)

I just wanted to let people know that I had posted a fairly non-technical overview of the use of principal components analysis in statistical modeling at:

Principal Components in Modeling

I have posted MATLAB source code for a routine, DeltaRule, which trains a single artificial neuron using the delta rule.  This code is available at MATLAB Central's File Exchange:

DeltaRule

Technical details:

Learning rule: incremental delta rule
Learning Rate: constant
Transfer function: logistic
Exemplar presentation order: random, by training epoch

Use 'help DeltaRule' for further details.

Hi..

I need to do a project where the number of call arrivals in a call centre has to be forecasted. I am new to datamining but I think neural netwrks can be used.. but i am not sure which type of neural nw to use or the tool to use. If anyone can suggest any other tool for forecasting apart from neural networks it will be helpful. kindly help plz.. 

Hello Data Miners!

 I have been reading about Data Mining in preperation for my assignment titled 'How are data fusion and data mining used to improve the effectiveness of direct marketing?', as you are all no doubt the tip top brains of Data Mining, I was wondering if you could point me in the direction of anything useful you can see for my assignment, I have currently been reading 'Mastering Data Mining' and 'Data Mining Cookbook'.

Thank you all! 

-Meowth

Well, i found C4.5 in C and even couldn't get it work. Does anyone know where can i get the code? Or please, just send it to my e-mail aeroshik@yandex.ru.

And may be some one has got source in Delphi? I'd also like to have it )

It would be great if you help me!

can any one provide me with a sample code for converting  a BSQ(band sequential format) image to bSQ(bit sequential format)....??

am working on data mining project which is about mining association rules for spatial data using p-trees...

Hi.

I need to make a project on "image classifiers using data miningclassification techniques" as a final year project of B.E. I am completely lostas what to do and how to begin with it. Any help will be reallyappreciated.

Navin