Expo:01

Aim: This experiment illeuserates some of the basic data preprocessing

operation that can be performed using WEKA explorer. The sample data set used

for the example is the student data unavailable in arff format.

steps involved in this experiment:

Step 1: leading the data: We can lead the data set into welke by clicking

on open button in preprocessing interface and selecting the appropriate

bile:

stepa: once the data is loaded wetta will recognize the attributes and during

the scan of the data weka will compute some basic strategies on each attribute.

The left panel in the above figure shows the list of the recognized

top panel indicates the name of the base relation

(61) table and the current working relation (which are same initially).

attributes

while the

attribute in the left panel will show the

on the attellbuter for the categorical attributes the

feach attribute value. l.e., shown while for continuous

can obtain min man, mean, standard deviation and

Step 3: Click on a

basis statitic

to

fequency

attributes

deviation etc.

we

Step 4:

The variation in the night button panel

night button panel in the form of

Cross tabulation acron two attributes.

Note: We can select another attributes using the drop down list.

Step 5;

Selecting (0)

filtering attributes.

Data set de Student. auff.

@relation student.

@attribute age [<30, 30-40, 7407

@attribute income { low, medium, high &

@attribute Student { yes, no}.

@attribute credit rating { fair, excellent}

@attribute buy, spc. [yes, no}

@ dala

<30, high, no, fair, no

<30, high, no, excellent,

E, no

30-40, high, no, fair, yes.

>40, medium, no, fair, yes.

>40, low, yes, fair, yes.

>40, low, yes, excellent.

no

30-40, low, yes, excellent, yes.

<30, medium, no, fair, no

<30, low, yes, fair, no

>40, medium, yes, excellent, yes

30, medium, yes, excellent, yes,

30-40, medium, no, excellent, yes

30-40, high, yes, fair, yes

>40, medium, no, excellent, no

%.

excellent, '