This paper reviews the state
-
of
-
the
-
art and the art
-
of
-
the
-
practice of
the classification machine
learning algorithms. In addition, th
is paper proposes a novel input
-
output relation classification and testing
strategy called Minimum Maximum Strategy (MMS). Internally, MMS derives the classification rules based
on minimum
-
maxi
mum values of attributes for each class till all entries in a
data set
are covered at least one.
In doing so, MMS achieves 100% classification accuracy as well as mining the
data set
which facilitate
building the classification model. Moreover, unlike othe
r existing algorithm MMS generates instances for
testing based on
the
boundary value analysis. As a proof of concept, MMS is used to build a classifier and
test instances for the famous IRIS
data set
. Encouraging results are obtained from experimentations on
the
accuracy against well
-
known classification algorithms as well as the effectiveness of the test data generated
by the MMS. Finally, it should be mentioned that all experiments are done using th
e WEKA machine
learning tool.
Abstract
This paper reviews the state
-
of
-
the
-
art and the art
-
of
-
the
-
practice of
the classification machine
learning algorithms. In addition, th
is paper proposes a novel input
-
output relation classification and testing
strategy called Minimum Maximum Strategy (MMS). Internally, MMS derives the classification rules based
on minimum
-
maxi
mum values of attributes for each class till all entries in a
data set
are covered at least one.
In doing so, MMS achieves 100% classification accuracy as well as mining the
data set
which facilitate
building the classification model. Moreover, unlike othe
r existing algorithm MMS generates instances for
testing based on
the
boundary value analysis. As a proof of concept, MMS is used to build a classifier and
test instances for the famous IRIS
data set
. Encouraging results are obtained from experimentations on
the
accuracy against well
-
known classification algorithms as well as the effectiveness of the test data generated
by the MMS. Finally, it should be mentioned that all experiments are done using th
e WEKA machine
learning tool.
Publication Date
8/1/2015
Publisher
International Journal of Computing Academic Research (IJCAR)
ا.د. محمد عصام يونس | Mohammed I. Younis | 13967