weka3.6 with LibSVM

Step 1: download LibSVM
https://github.com/cjlin1/libsvm

Step2: unzip the zip file libsvm-master.zip,
  and then find the libsvm.jar in /where you unzip/libsvm-master/java

Step3: copy libsvm.jar into your Weka folder
  ex: in my path is D:\Weka3-6\

Step4: set up the CLASSPATH in your environment or in RunWeka.ini
in your environment
  in Windows:
    In the Control Panel click on System (or right click on My Computer and select Properties) and then go       to the Advanced tab. There you will find a button called Environment Variables, click it.
    Enter the "CLASSPATH" for the variable and add this value "D:\Weka3-6\libsvm.jar" after ";" if you have     other values in CLASSPATH

  DOS command:
    set CLASSPATH=%CLASSPATH%;D:\Weka3-6\libsvm.jar;

  in Linux:
    export CLASSPATH=$CLASSPATH: where your libsvm.jar
    if i put it in /home/user
    export CLASSPATH=$CLASSPATH:/home/user/libsvm.jar

in RunWeka.ini:
  in Windows:
    open RunWeka.ini with any text editor, you can find
    cp=%CLASSPATH%; in the last line
    add your path of libsvm.jar after ";"

    cp=%CLASSPATH%;D:\Weka3-6\libsvm.jar
    or
    cp=%CLASSPATH%;./libsvm.jar

Using Sparse ARFF files as the input of weka association rule

the format is as below test.arff

 @relation test
 @attribute a {y}
 @attribute b {y}
 @attribute c {y}
 @attribute d {y}
 @attribute e {y}
 @attribute f {y}
 @attribute g {y}
 @attribute h {y}

@data
{1 y,3 y,5 y}
{2 y,3 y,5 y}
{2 y,6 y}
{1 y,3 y,5 y}
{3 y,5 y,7 y}
{1 y,2 y,3 y}
{2 y,4 y,5 y}
{2 y,3 y,5 y}
{3 y,5 y,7 y}
{1 y,2 y}
{1 y,5 y,7 y}

Weka FP Growth dataset

Weka FPGrowth needs Binary attributes, arff form likes this:


@relation FPGrowth dataset

@attribute a {1,0}
@attribute b {1,0}
@attribute c {1,0}

@data
0,0,0
0,0,1
0,1,0
0,1,1
1,0,0
1,0,1
1,1,0
1,1,1