Data Mining Techniques With Intelligent Systems

Running Head: IS FOR ANALYTICS
0
Data Mining Techniques
with IS
Intelligent Systems for Analytics
(Student Details: )
1/15/2020

IS FOR ANALYTICS
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Contents
Introduction................................................................................................................................2
Data Mining Techniques with Intelligent Systems....................................................................2
Basic DM Techniques and Algorithms......................................................................................3
Genetic algorithms.................................................................................................................4
Artificial neural networks......................................................................................................4
Decision trees.........................................................................................................................4
Rule induction........................................................................................................................4
Nearest neighbour method.....................................................................................................4
Data visualization...................................................................................................................4
Business Intelligence (BI) using DM techniques...................................................................5
Use of Data Mining in Business Analytics (BA)...................................................................5
Applications of DM with IS...................................................................................................5
Conclusion..................................................................................................................................6
References..................................................................................................................................6

IS FOR ANALYTICS
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Introduction
This research report is based on research on ‘Intelligent Systems for Analytics’ (ISA) with
some specific area into Intelligent Systems (IS). In general, IS is the system that incorporates
intelligence in useful applications being handled by modern machines. In this context, IS
typically performs optimization as well as search along with extended learning abilities.
Specifically, the report will talk about Data Mining (DM) while exploring different methods
and techniques with the help of IS. Here, DM refers to the practice of evaluating large-level
prevailing databases for further generating completely new information 1. It can be said that
the process of discovering hidden value into the complete data warehouse is known as DM.
In other words, DM is a new technology with high potential for helping modern firms in
order to focus on important facts and information within data warehouses 2. While discussing
IS, the report will narrate how DM tools anticipate upcoming trends as well as behaviours
while enabling businesses to make knowledge-driven and proactive decisions.
Data Mining Techniques with Intelligent Systems
Firstly, the concept of DM needs to be defined as the process of discovering patterns into big
data-sets contains methods at the overlapping of statistics, database systems, and machine
learning 3. Thus, DM can effectively use IS which is an advanced machine learning. IS is
able to learn, perceive and thereby solve critical issues with enhanced accuracy. In addition to
that, there are so many general technologies which are available in the market as well as used
in real-world use like Facebook, Alexa, Siri, self-driving cars and many more 4. In this way,
data mining techniques while using ISs are being discussed and explored here. DM is able to
find useful patterns from a huge amount of data and this process of mining of data becomes
more efficient when IS is integrated into DM techniques. In the process of knowledge
discovery, knowledge mining through data, as well as knowledge extraction, IS plays a vital
role in pattern and data analysis 4.