TY  - JOUR
T1  - Enhanced Bio-Inspired Algorithm for Disease Diagnosis
AU - Gitanjali, J. AU - Subhashini, R. 
JO  - Journal of Engineering and Applied Sciences
VL  - 15
IS  - 16
SP  - 3024
EP  - 3031
PY  - 2020
DA  - 2001/08/19
SN  - 1816-949x
DO  - jeasci.2020.3024.3031
UR  - https://makhillpublications.co/view-article.php?doi=jeasci.2020.3024.3031
KW  - Decision tree
KW  -feature extraction
KW  -firefly algorithm
KW  -hybridization
KW  -accuracy
AB  - Datasets are gathered for different diseases and
then the feature is extracted using dimensionality
reduction techniques. After the attributes are reduced, the
attributes are used to test and train the data using decision
tree classification algorithm techniques. The various
decision tree algorithms are also used to find the accuracy
for each diseases and then hybridization techniques are
used to solve the problem which is then used to create
upgraded yield. Metaheuristic is generally a search
algorithm which solves the optimization problems that
provides the best solution from the available solutions. It
provides a better solution with less effort compared with
other algorithms. One of the recent trend is hybrid
optimization methods. Hybridization of metaheuristics are
nothing but combining two bio-inspired algorithms. It
improves algorithmic performance in a more efficient way
to solve the problems. Hybridization techniques extracts
the strengths from the combination of each algorithm.
ER  -