Name of Student : G. Uday Shankar
Course Information :
Submitted to : Prof. Darcel Tolliver.
University Name : Virginia International University.
Date : 26/6/2016.
In present days, storing data became an easy work but t
What Is Data Quality and Why Should
Caring about data quality is key to safeguarding and improving it. As stated,
this sounds like a very obvious proposition. But can we, as the expression goes,
recognize it when we see it? Considerable analysi
4Classification and Prediction (6hrs)
4.1 What is classification? What is prediction?
4.2 Issues regarding classification and prediction
4.3 Classification by decision tree induction
4.4 Bayesian classification
4.5 Classification by back propagation
Commercial Data Mining Systems:
Whether you are brand new to data mining or working on your tenth
predictive analytics project, Commercial Data Mining will be there for you
as an accessible reference outlining the entire process and related th
Data Preprocessing 2.8 Exercises 2.1. Data quality can be assessed in terms of accuracy, completeness,
and consistency. Propose two other dimensions of data quality. Answer: Other dimensions that can be
used to assess the quality of data include timelines
Discuss Data cube computation methods.
In OLAP systems, a data cube is a way of organizing data in N-dimensions so as to
perform analysis over some measure of interest. The data cube is used for conveniently
supporting multiple aggregates in OLAP database
Secure Mining of Association Rules in Horizontally Distributed Databases
We propose a protocol for secure mining of association rules in horizontally distributed
databases. The current leading protocol is that of Kantarcioglu and Clifton . Ou
Frequent Item set Mining
Frequent item set mining is an interesting branch of data mining that spotlights on taking
a gander at arrangements of activities or occasions, for instance the request in which we get
dressed. Shirt first? Pants first? Socks seco
Summer I - 2016 - Paper Critique (Webinar)
The Future of Data Warehousing
ETL Will Never be the Same.
Traditional data warehouse ETL has become too slow, too complicated,
and too expensive to address the torrent of new data sources and ne