TROPHIC DIATOM CLASSIFICATION USING NAÏVE BAYES
Date Issued
2013
Author(s)
Abstract
Knowledge discovery has been used in many different type of
analysis and data types which lead to increased understanding
of many natural processes and phenomena. This is why this
process is important in the area of analysing environmental
data. The topic and the goal of the paper is to used this
process and the information contained in the measured data
for given lake ecosystem and extract that information in an
understandable form. This research aims to assess the
relationships between the diatoms and the indicators of the
environment using Naïve Bayes method learning technique.
The diatoms are taken into account because they are ideal
indicators of certain physical-chemical parameters and they
can be classified into one of the trophic quality classes
(TQCs). Before the algorithm processes the data, the input
dataset is discretised. Then using the Naïve Bayes technique,
several models for each TQC are obtained, presented and
discussed. Then the obtained knowledge is verified with
existing diatom ecological preference. Directions of future
research and improvement for using this method for
environmental data are given at the conclusion of the paper.
analysis and data types which lead to increased understanding
of many natural processes and phenomena. This is why this
process is important in the area of analysing environmental
data. The topic and the goal of the paper is to used this
process and the information contained in the measured data
for given lake ecosystem and extract that information in an
understandable form. This research aims to assess the
relationships between the diatoms and the indicators of the
environment using Naïve Bayes method learning technique.
The diatoms are taken into account because they are ideal
indicators of certain physical-chemical parameters and they
can be classified into one of the trophic quality classes
(TQCs). Before the algorithm processes the data, the input
dataset is discretised. Then using the Naïve Bayes technique,
several models for each TQC are obtained, presented and
discussed. Then the obtained knowledge is verified with
existing diatom ecological preference. Directions of future
research and improvement for using this method for
environmental data are given at the conclusion of the paper.
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