SlideShare a Scribd company logo
1 of 16
Matlab: Procedures and Functions
Script files Script files, also called M- files as they have extension .m, make MATLAB programming much more efficient than entering individual commands at the command prompt. A script file consists of MATLAB commands that together perform a specific task. The M-file is a text file which can be created and edited by any plain text editor like Notepad, emacs or the built-in MATLAB editor. 
Script files Script files, also called M- files as they have extension .m, make MATLAB programming much more efficient than entering individual commands at the command prompt. A script file consists of MATLAB commands that together perform a specific task. The M-file is a text file which can be created and edited by any plain text editor like Notepad, emacs or the built-in MATLAB editor. 
Script files Here’s an example of what a script file looks like:
Script files Important commands: for- To print "Hello World" 10 times write ,[object Object]
disp('Hello World')
 end,[object Object]
a = b + 1
elseif a > b
 a = b - 1
else a = b
 end,[object Object]
 User Defined Functions An example of a function:
String Handling Creating strings Strings are matrices with character elements. The simplest way to create a string is to use it on the left side of an equal sign where the right side of the equal sign is an expression that evaluates to a string. String constants (literals) are enclosed in single quotes. The following example shows how to create string variables. >> first = 'John';  >> last = 'Coltrane';  >> name = [first,' ',last]
String Handling >> string='This is a string‘ >> string(3) % gives the third element in the variable words.  ans = i >> string(2)='t' % replaces the second element in the vector with t.
String Handling >> Y= input('Please type something here: ','s');  % Matlab expects a  number, string or a matrix from the keyboard.  % The second argument says the returned variable should be a string. >> disp('The name is: '), disp(x)  % gives text as output and the value of x.

More Related Content

What's hot (18)

Link List
Link ListLink List
Link List
 
Singly link list
Singly link listSingly link list
Singly link list
 
Getting started with c++
Getting started with c++Getting started with c++
Getting started with c++
 
Linked list
Linked listLinked list
Linked list
 
Programming with matlab session 3 notes
Programming with matlab session 3 notesProgramming with matlab session 3 notes
Programming with matlab session 3 notes
 
Singly & Circular Linked list
Singly & Circular Linked listSingly & Circular Linked list
Singly & Circular Linked list
 
Pointers in c v5 12102017 1
Pointers in c v5 12102017 1Pointers in c v5 12102017 1
Pointers in c v5 12102017 1
 
Strings
StringsStrings
Strings
 
C programming session 09
C programming session 09C programming session 09
C programming session 09
 
Circular link list.ppt
Circular link list.pptCircular link list.ppt
Circular link list.ppt
 
Linked lists a
Linked lists aLinked lists a
Linked lists a
 
linked list
linked listlinked list
linked list
 
POINTERS IN C MRS.SOWMYA JYOTHI.pdf
POINTERS IN C MRS.SOWMYA JYOTHI.pdfPOINTERS IN C MRS.SOWMYA JYOTHI.pdf
POINTERS IN C MRS.SOWMYA JYOTHI.pdf
 
Doubly Link List
Doubly Link ListDoubly Link List
Doubly Link List
 
Linear data structure concepts
Linear data structure conceptsLinear data structure concepts
Linear data structure concepts
 
Arrays in c_language
Arrays in c_language Arrays in c_language
Arrays in c_language
 
Arrays in c++
Arrays in c++Arrays in c++
Arrays in c++
 
Strings
StringsStrings
Strings
 

Viewers also liked

Viewers also liked (20)

Data Applied:Decision Trees
Data Applied:Decision TreesData Applied:Decision Trees
Data Applied:Decision Trees
 
Excel Datamining Addin Intermediate
Excel Datamining Addin IntermediateExcel Datamining Addin Intermediate
Excel Datamining Addin Intermediate
 
MED dra Coding -MSSO
MED dra Coding -MSSOMED dra Coding -MSSO
MED dra Coding -MSSO
 
RapidMiner: Advanced Processes And Operators
RapidMiner:  Advanced Processes And OperatorsRapidMiner:  Advanced Processes And Operators
RapidMiner: Advanced Processes And Operators
 
Matlab Importing Data
Matlab Importing DataMatlab Importing Data
Matlab Importing Data
 
Control Statements in Matlab
Control Statements in  MatlabControl Statements in  Matlab
Control Statements in Matlab
 
Eugene SRTS Program
Eugene SRTS ProgramEugene SRTS Program
Eugene SRTS Program
 
LISP:Predicates in lisp
LISP:Predicates in lispLISP:Predicates in lisp
LISP:Predicates in lisp
 
MySql:Basics
MySql:BasicsMySql:Basics
MySql:Basics
 
XL-MINER:Partition
XL-MINER:PartitionXL-MINER:Partition
XL-MINER:Partition
 
2008 IEDM presentation
2008 IEDM presentation2008 IEDM presentation
2008 IEDM presentation
 
MySql:Introduction
MySql:IntroductionMySql:Introduction
MySql:Introduction
 
System Init
System InitSystem Init
System Init
 
Festivals Refuerzo
Festivals RefuerzoFestivals Refuerzo
Festivals Refuerzo
 
Presentazione oroblu
Presentazione orobluPresentazione oroblu
Presentazione oroblu
 
Apresentação Red Advisers
Apresentação Red AdvisersApresentação Red Advisers
Apresentação Red Advisers
 
SPSS: Data Editor
SPSS: Data EditorSPSS: Data Editor
SPSS: Data Editor
 
XL-Miner: Timeseries
XL-Miner: TimeseriesXL-Miner: Timeseries
XL-Miner: Timeseries
 
Data Applied: Developer Quicklook
Data Applied: Developer QuicklookData Applied: Developer Quicklook
Data Applied: Developer Quicklook
 
Jive Clearspace Best#2598 C8
Jive  Clearspace  Best#2598 C8Jive  Clearspace  Best#2598 C8
Jive Clearspace Best#2598 C8
 

Similar to Matlab Procedures and Functions Guide

Similar to Matlab Procedures and Functions Guide (20)

Matlab Basic Tutorial
Matlab Basic TutorialMatlab Basic Tutorial
Matlab Basic Tutorial
 
Introduction to matlab
Introduction to matlabIntroduction to matlab
Introduction to matlab
 
Introduction to matlab
Introduction to matlabIntroduction to matlab
Introduction to matlab
 
Matlab Manual
Matlab ManualMatlab Manual
Matlab Manual
 
Brief Introduction to Matlab
Brief  Introduction to MatlabBrief  Introduction to Matlab
Brief Introduction to Matlab
 
MatlabIntro.ppt
MatlabIntro.pptMatlabIntro.ppt
MatlabIntro.ppt
 
MatlabIntro.ppt
MatlabIntro.pptMatlabIntro.ppt
MatlabIntro.ppt
 
MatlabIntro.ppt
MatlabIntro.pptMatlabIntro.ppt
MatlabIntro.ppt
 
Matlab intro
Matlab introMatlab intro
Matlab intro
 
MatlabIntro.ppt
MatlabIntro.pptMatlabIntro.ppt
MatlabIntro.ppt
 
PHP Web Programming
PHP Web ProgrammingPHP Web Programming
PHP Web Programming
 
Matlab strings
Matlab stringsMatlab strings
Matlab strings
 
Pattern matching programs
Pattern matching programsPattern matching programs
Pattern matching programs
 
Introduction to matlab
Introduction to matlabIntroduction to matlab
Introduction to matlab
 
Ch1
Ch1Ch1
Ch1
 
Unitii classnotes
Unitii classnotesUnitii classnotes
Unitii classnotes
 
Ch09
Ch09Ch09
Ch09
 
Dsp lab _eec-652__vi_sem_18012013
Dsp lab _eec-652__vi_sem_18012013Dsp lab _eec-652__vi_sem_18012013
Dsp lab _eec-652__vi_sem_18012013
 
Dsp lab _eec-652__vi_sem_18012013
Dsp lab _eec-652__vi_sem_18012013Dsp lab _eec-652__vi_sem_18012013
Dsp lab _eec-652__vi_sem_18012013
 
Matlab guide
Matlab guideMatlab guide
Matlab guide
 

More from DataminingTools Inc

AI: Introduction to artificial intelligence
AI: Introduction to artificial intelligenceAI: Introduction to artificial intelligence
AI: Introduction to artificial intelligenceDataminingTools Inc
 
Data Mining: Text and web mining
Data Mining: Text and web miningData Mining: Text and web mining
Data Mining: Text and web miningDataminingTools Inc
 
Data Mining: Mining stream time series and sequence data
Data Mining: Mining stream time series and sequence dataData Mining: Mining stream time series and sequence data
Data Mining: Mining stream time series and sequence dataDataminingTools Inc
 
Data Mining: Mining ,associations, and correlations
Data Mining: Mining ,associations, and correlationsData Mining: Mining ,associations, and correlations
Data Mining: Mining ,associations, and correlationsDataminingTools Inc
 
Data Mining: Graph mining and social network analysis
Data Mining: Graph mining and social network analysisData Mining: Graph mining and social network analysis
Data Mining: Graph mining and social network analysisDataminingTools Inc
 
Data warehouse and olap technology
Data warehouse and olap technologyData warehouse and olap technology
Data warehouse and olap technologyDataminingTools Inc
 

More from DataminingTools Inc (20)

Terminology Machine Learning
Terminology Machine LearningTerminology Machine Learning
Terminology Machine Learning
 
Techniques Machine Learning
Techniques Machine LearningTechniques Machine Learning
Techniques Machine Learning
 
Machine learning Introduction
Machine learning IntroductionMachine learning Introduction
Machine learning Introduction
 
Areas of machine leanring
Areas of machine leanringAreas of machine leanring
Areas of machine leanring
 
AI: Planning and AI
AI: Planning and AIAI: Planning and AI
AI: Planning and AI
 
AI: Logic in AI 2
AI: Logic in AI 2AI: Logic in AI 2
AI: Logic in AI 2
 
AI: Logic in AI
AI: Logic in AIAI: Logic in AI
AI: Logic in AI
 
AI: Learning in AI 2
AI: Learning in AI 2AI: Learning in AI 2
AI: Learning in AI 2
 
AI: Learning in AI
AI: Learning in AI AI: Learning in AI
AI: Learning in AI
 
AI: Introduction to artificial intelligence
AI: Introduction to artificial intelligenceAI: Introduction to artificial intelligence
AI: Introduction to artificial intelligence
 
AI: Belief Networks
AI: Belief NetworksAI: Belief Networks
AI: Belief Networks
 
AI: AI & Searching
AI: AI & SearchingAI: AI & Searching
AI: AI & Searching
 
AI: AI & Problem Solving
AI: AI & Problem SolvingAI: AI & Problem Solving
AI: AI & Problem Solving
 
Data Mining: Text and web mining
Data Mining: Text and web miningData Mining: Text and web mining
Data Mining: Text and web mining
 
Data Mining: Outlier analysis
Data Mining: Outlier analysisData Mining: Outlier analysis
Data Mining: Outlier analysis
 
Data Mining: Mining stream time series and sequence data
Data Mining: Mining stream time series and sequence dataData Mining: Mining stream time series and sequence data
Data Mining: Mining stream time series and sequence data
 
Data Mining: Mining ,associations, and correlations
Data Mining: Mining ,associations, and correlationsData Mining: Mining ,associations, and correlations
Data Mining: Mining ,associations, and correlations
 
Data Mining: Graph mining and social network analysis
Data Mining: Graph mining and social network analysisData Mining: Graph mining and social network analysis
Data Mining: Graph mining and social network analysis
 
Data warehouse and olap technology
Data warehouse and olap technologyData warehouse and olap technology
Data warehouse and olap technology
 
Data Mining: Data processing
Data Mining: Data processingData Mining: Data processing
Data Mining: Data processing
 

Recently uploaded

Advanced Test Driven-Development @ php[tek] 2024
Advanced Test Driven-Development @ php[tek] 2024Advanced Test Driven-Development @ php[tek] 2024
Advanced Test Driven-Development @ php[tek] 2024Scott Keck-Warren
 
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure service
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure serviceWhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure service
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure servicePooja Nehwal
 
Key Features Of Token Development (1).pptx
Key  Features Of Token  Development (1).pptxKey  Features Of Token  Development (1).pptx
Key Features Of Token Development (1).pptxLBM Solutions
 
Artificial intelligence in the post-deep learning era
Artificial intelligence in the post-deep learning eraArtificial intelligence in the post-deep learning era
Artificial intelligence in the post-deep learning eraDeakin University
 
Pigging Solutions Piggable Sweeping Elbows
Pigging Solutions Piggable Sweeping ElbowsPigging Solutions Piggable Sweeping Elbows
Pigging Solutions Piggable Sweeping ElbowsPigging Solutions
 
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreterPresentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreternaman860154
 
Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...
Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...
Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...shyamraj55
 
Azure Monitor & Application Insight to monitor Infrastructure & Application
Azure Monitor & Application Insight to monitor Infrastructure & ApplicationAzure Monitor & Application Insight to monitor Infrastructure & Application
Azure Monitor & Application Insight to monitor Infrastructure & ApplicationAndikSusilo4
 
Unblocking The Main Thread Solving ANRs and Frozen Frames
Unblocking The Main Thread Solving ANRs and Frozen FramesUnblocking The Main Thread Solving ANRs and Frozen Frames
Unblocking The Main Thread Solving ANRs and Frozen FramesSinan KOZAK
 
How to Remove Document Management Hurdles with X-Docs?
How to Remove Document Management Hurdles with X-Docs?How to Remove Document Management Hurdles with X-Docs?
How to Remove Document Management Hurdles with X-Docs?XfilesPro
 
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...Integration and Automation in Practice: CI/CD in Mule Integration and Automat...
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...Patryk Bandurski
 
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmaticsKotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmaticscarlostorres15106
 
Swan(sea) Song – personal research during my six years at Swansea ... and bey...
Swan(sea) Song – personal research during my six years at Swansea ... and bey...Swan(sea) Song – personal research during my six years at Swansea ... and bey...
Swan(sea) Song – personal research during my six years at Swansea ... and bey...Alan Dix
 
CloudStudio User manual (basic edition):
CloudStudio User manual (basic edition):CloudStudio User manual (basic edition):
CloudStudio User manual (basic edition):comworks
 
Breaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountBreaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountPuma Security, LLC
 
Hyderabad Call Girls Khairatabad ✨ 7001305949 ✨ Cheap Price Your Budget
Hyderabad Call Girls Khairatabad ✨ 7001305949 ✨ Cheap Price Your BudgetHyderabad Call Girls Khairatabad ✨ 7001305949 ✨ Cheap Price Your Budget
Hyderabad Call Girls Khairatabad ✨ 7001305949 ✨ Cheap Price Your BudgetEnjoy Anytime
 
How to convert PDF to text with Nanonets
How to convert PDF to text with NanonetsHow to convert PDF to text with Nanonets
How to convert PDF to text with Nanonetsnaman860154
 
Benefits Of Flutter Compared To Other Frameworks
Benefits Of Flutter Compared To Other FrameworksBenefits Of Flutter Compared To Other Frameworks
Benefits Of Flutter Compared To Other FrameworksSoftradix Technologies
 

Recently uploaded (20)

Advanced Test Driven-Development @ php[tek] 2024
Advanced Test Driven-Development @ php[tek] 2024Advanced Test Driven-Development @ php[tek] 2024
Advanced Test Driven-Development @ php[tek] 2024
 
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure service
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure serviceWhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure service
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure service
 
Key Features Of Token Development (1).pptx
Key  Features Of Token  Development (1).pptxKey  Features Of Token  Development (1).pptx
Key Features Of Token Development (1).pptx
 
Artificial intelligence in the post-deep learning era
Artificial intelligence in the post-deep learning eraArtificial intelligence in the post-deep learning era
Artificial intelligence in the post-deep learning era
 
Pigging Solutions Piggable Sweeping Elbows
Pigging Solutions Piggable Sweeping ElbowsPigging Solutions Piggable Sweeping Elbows
Pigging Solutions Piggable Sweeping Elbows
 
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreterPresentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreter
 
Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...
Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...
Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...
 
Azure Monitor & Application Insight to monitor Infrastructure & Application
Azure Monitor & Application Insight to monitor Infrastructure & ApplicationAzure Monitor & Application Insight to monitor Infrastructure & Application
Azure Monitor & Application Insight to monitor Infrastructure & Application
 
The transition to renewables in India.pdf
The transition to renewables in India.pdfThe transition to renewables in India.pdf
The transition to renewables in India.pdf
 
Unblocking The Main Thread Solving ANRs and Frozen Frames
Unblocking The Main Thread Solving ANRs and Frozen FramesUnblocking The Main Thread Solving ANRs and Frozen Frames
Unblocking The Main Thread Solving ANRs and Frozen Frames
 
How to Remove Document Management Hurdles with X-Docs?
How to Remove Document Management Hurdles with X-Docs?How to Remove Document Management Hurdles with X-Docs?
How to Remove Document Management Hurdles with X-Docs?
 
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...Integration and Automation in Practice: CI/CD in Mule Integration and Automat...
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...
 
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmaticsKotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
 
Swan(sea) Song – personal research during my six years at Swansea ... and bey...
Swan(sea) Song – personal research during my six years at Swansea ... and bey...Swan(sea) Song – personal research during my six years at Swansea ... and bey...
Swan(sea) Song – personal research during my six years at Swansea ... and bey...
 
CloudStudio User manual (basic edition):
CloudStudio User manual (basic edition):CloudStudio User manual (basic edition):
CloudStudio User manual (basic edition):
 
Breaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountBreaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path Mount
 
Hyderabad Call Girls Khairatabad ✨ 7001305949 ✨ Cheap Price Your Budget
Hyderabad Call Girls Khairatabad ✨ 7001305949 ✨ Cheap Price Your BudgetHyderabad Call Girls Khairatabad ✨ 7001305949 ✨ Cheap Price Your Budget
Hyderabad Call Girls Khairatabad ✨ 7001305949 ✨ Cheap Price Your Budget
 
Vulnerability_Management_GRC_by Sohang Sengupta.pptx
Vulnerability_Management_GRC_by Sohang Sengupta.pptxVulnerability_Management_GRC_by Sohang Sengupta.pptx
Vulnerability_Management_GRC_by Sohang Sengupta.pptx
 
How to convert PDF to text with Nanonets
How to convert PDF to text with NanonetsHow to convert PDF to text with Nanonets
How to convert PDF to text with Nanonets
 
Benefits Of Flutter Compared To Other Frameworks
Benefits Of Flutter Compared To Other FrameworksBenefits Of Flutter Compared To Other Frameworks
Benefits Of Flutter Compared To Other Frameworks
 

Matlab Procedures and Functions Guide

  • 2. Script files Script files, also called M- files as they have extension .m, make MATLAB programming much more efficient than entering individual commands at the command prompt. A script file consists of MATLAB commands that together perform a specific task. The M-file is a text file which can be created and edited by any plain text editor like Notepad, emacs or the built-in MATLAB editor. 
  • 3. Script files Script files, also called M- files as they have extension .m, make MATLAB programming much more efficient than entering individual commands at the command prompt. A script file consists of MATLAB commands that together perform a specific task. The M-file is a text file which can be created and edited by any plain text editor like Notepad, emacs or the built-in MATLAB editor. 
  • 4. Script files Here’s an example of what a script file looks like:
  • 5.
  • 7.
  • 8. a = b + 1
  • 10. a = b - 1
  • 12.
  • 13. User Defined Functions An example of a function:
  • 14. String Handling Creating strings Strings are matrices with character elements. The simplest way to create a string is to use it on the left side of an equal sign where the right side of the equal sign is an expression that evaluates to a string. String constants (literals) are enclosed in single quotes. The following example shows how to create string variables. >> first = 'John'; >> last = 'Coltrane'; >> name = [first,' ',last]
  • 15. String Handling >> string='This is a string‘ >> string(3) % gives the third element in the variable words. ans = i >> string(2)='t' % replaces the second element in the vector with t.
  • 16. String Handling >> Y= input('Please type something here: ','s'); % Matlab expects a number, string or a matrix from the keyboard. % The second argument says the returned variable should be a string. >> disp('The name is: '), disp(x) % gives text as output and the value of x.
  • 17. String Handling Also, different formats can be converted to ‘strings’ and vice verse. Here are some examples of functions that help in converting between different formats: int2str(n)  Converts an integer n to a string hex2num(hstr)  Converts hexadecimal number hstr to a float. hex2dec(hstr)  Converts hexadecimal string to decimal integer. dec2hex(n)  Converts decimal integer to hexadecimal string. bin2dec(str)  Converts binary string to decimal integer. mat2str(A,n)  Convert a 2-D matrix to a string in MATLAB syntax.
  • 18. String Handling There are several functions available to manipulate or fetch appropriate data from strings: blanks(n)  Gives a string with n blanks deblank(str)  Subtracts all blanks at the end of the string. lower(str)  All letters are changed to small. upper(str)  All letters are changed to capital. ischar(str)  If string contains character => gives 1 in return, 0 otherwise.
  • 19. String Handling There are several functions available to manipulate or fetch appropriate data from strings: isletter(str(i))  If element number i in the string is a letter=> gives one in return. isspace(str)  True for white space characters. strcmp(str1,str2)  returns 1 if strings S1 and S2 are the same and 0 otherwise. strcmpi(str1,str2)  returns 1 if strings S1 and S2 are the same except forcase and 0 otherwise.
  • 20. String Handling There are several functions available to manipulate or fetch appropriate data from strings: strfind(str1,str2)  returns the starting indices of any occurrences of the string str2 in the string str1. findstr(str1,str2)  returns the starting indices of any occurrences of the shorter of the two strings in the longer.
  • 21. Visit more self help tutorials Pick a tutorial of your choice and browse through it at your own pace. The tutorials section is free, self-guiding and will not involve any additional support. Visit us at www.dataminingtools.net