In: Computer Science
Discuss the two estimation methods of classification-type data mining models while considering ANN as a classifier.
Data Mining is the process that is defined as the process of
extracting information from large amount of data. To simply say ,
data mining is mining knowledge from data.There are two forms of
data analysis that can be used for extracting models.
Classification
Prediction
Classification models are used to predict categorized parts of data
while prediction models are for continuous valued
functions.Classification is used to find out that,to which group of
data sets the data instance is related within a given dataset. This
is used for classifying data based on some constrains.By using
classification techniques in data mining we can retrieve a large
amount of data.Three main historical strands of research can be
identified: statistical, machine learning and neural network.All
the three concepts focuses on same objective that deviding as
classes.
Statistical Procedure Based Approach
This approach working in two phases. The first one is “classical”
phase that is concentrated on extension of Fisher’s early work
based on linear discrimination. The second, “modern” phase
concentrated on more flexible classes of models and provide a
classification rule. The main advantage with statistical approach
is it also applies probability of data not just classification.
Machine Learning Based Approach
Machine Learning is mainly focuses on computing procedures based on
logical or binary operations.Unlike statistic approach here we are
just concentrating on classification and should be focussed on
decision-tree approaches. These classification is capable of
retrieving the most complex problem given sufficient data. The main
aim of machine Learning approach to generate classifying
expressions simple enough to be understood.Here operation is
assumed without human interference.