Weka and Written Exercise | Analysis and Report

Running head: WEKA AMD WRITTEN EXERCISE-ANALYSIS AND REPORT 1
Weka and Written Exercise: Analysis and Report
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WEKA AMD WRITTEN EXERCISE-ANALYSIS AND REPORT 2
Weka and Written Exercise: Analysis and Report
Task 1: Weka Data Exploration
a) According to Smith (2015), instances are the individual independent examples of
kinds of things that can be learned from a dataset. On the contrary, attributes are
measuring aspects of an instances. As demonstrated below, the dataset has 768
instances and 9 attributes.
b) A class in a dataset represents a group of values is classified for analysis and
generation of frequency distribution ( Boels, Bakker, Wim , & Drijvers, 2016). Based
on Weka output shown below, the dataset has two classes: tested_negative and
tested_positive with 500 and 268 instances, respectively.
c) The dataset has 13 age groups with largest having 267 samples and smallest having 1
sample. Therefore, as shown below, the age group with the highest number of samples
is [21, 25,615].
Task 2: Working with a new Data File in Weka

WEKA AMD WRITTEN EXERCISE-ANALYSIS AND REPORT 3
a) After removal of petal_width attribute, the following is an overview of the iris.3D.rff
dataset:
b) The screenshot below shows histograms with default setting for each attribute in the
new dataset: