... BASED DATAMINING TECHNIQUES
The objective of datamining is to extract valuable information from one’s data, to discover the ‘hidden
gold’. In Decision Support Management terminology, datamining ... one search for patterns of information in data (Parsaye, 1997).
Figure 2: Rule Induction process
Data mining techniques are based on data retention and data distillation. Rule induction models ... process.
REFERENCES
[1] Akeel Al-Attar, 1998, DataMining – Beyond Algorithms’, http://www.attar.com/tutor /mining. htm.
[2] Berry, J. A. Michael; Linoff, Gordon, 1997, DataMining Techniques: For Marketing,...
... Series Data
Series data differs from the forms of data so far discussed mainly in the way in which the
data enfolds the information. The main difference is that the ordering of the data ... reason that series data has to be prepared differently from nonseries data.
There is a large difference between preparing data for modeling and actually modeling the
data. This book focuses ... Modeling Series Data
Given these tools for describing series data, how do they help with preparing the data for
modeling? There are two main approaches to modeling series data. One uses...
... optimized mining toolset, could not deal with a multiterabyte, 7000+
variable data set required on one mining project.
Another reason that high dimensionality presents difficulties for mining ... series data. Data visualization is a broad field in itself,
and there are many highly powerful tools for handling data that have superb visualization
capability. For small to moderate data sets, ... like. Does one of them seem to fit some
underlying trend in the data? If so, subtract it from the data. When graphed, does the
data fit the horizontal axis better? If yes, fine. If no, keep trying....
... the mining tool the customer had selected, causing repeated
mining software failures and system crashes during mining.
The data reduction methodology described above reduced the data ... density manifold stability.
But here is where data preparation steps into the data survey. The data survey
(Chapter 11) examines the data set as a whole from many different points of view. ... rather than data
preparation? Data preparation concentrates on transforming and adjusting variables’
values to ensure maximum information exposure. Data surveying concentrates on
examining a...
... do with data mining? The whole purpose of the data survey is to help
the miner draw a high-level map of the territory. With this map, a data miner discovers the
general shape of the data, as ... can be used to examine data as
instances, data as variables, the data set as a whole, and various parts of a data set.
Entropy and mutual information are used to evaluate data in many ways. Some ... Such data has a perspective.
When mining perspectival data sets, it is very important to use nonperspectival test and
evaluation sets. With the best of intentions, the miningdata has...
...
11.4.1 Confidence and Sufficient Data
A data set may be inadequate for mining purposes simply because it does not truly
represent the population. If a data set doesn’t represent the population ... properly part of the data survey. The
survey only looks at and measures the data set presented. While it provides information
about the data set, it does not manipulate the data in any way, exactly ... of the instances can be assembled into a data set, and that data set examined for
similarity to the training data set, but that only tells you that the data set now assembled
was or wasn’t drawn...
... statisticians
and data miners still have different philosophical approaches to modeling from data.
12.1.3 DataMining vs. Exploratory Data Analysis
Exploratory data analysis (EDA) ... try data mining, a new discipline to her, but one that had received
good reviews in the business press. How did the datamining project differ from the
statistical approach?
Data mining ...
relationships from this data that are then to be applied to other similar data. Whatever can
be discovered in this data is sufficient, since it works in this data set, and there is no other
data set to...
... test data set (top) and an 85.8283% accuracy
in the test data for the prepared data set (bottom).
12.4 Practical Use of Data Preparation and Prepared Data
How does a miner use data ...
working with the data. When the data is easy to model, better models come out faster,
which is the technical purpose of data preparation. How does data preparation make the
data easier to work ...
Data preparation looked at here has dealt with data in the form collected in mainly
corporate databases. Clearly this is where the focus is today, and it is also the sort of data
on which data...
... what does data preparation alone achieve in this
data set? In order to demonstrate that, we will look at two models of the data one on
prepared data, and the other on unprepared data.
...
Data preparation looked at here has dealt with data in the form collected in mainly
corporate databases. Clearly this is where the focus is today, and it is also the sort of data
on which data ... datamining tools and data modeling tools focus.
The near future will see the development of automated data preparation tools for series
data. Approaches for automated series data preparation...
... required
for
mining distributed
data,
handling
the
meta -data
and the
mappings required
for
mining
the
distributed
data.
Spatial
database
systems
involve
spatial
data
-
that
... algorithms
and is
termed
distributed
data
mining
[51].
Traditional
data
mining algorithms require
all
data
to be
mined
in a
single,
centralized
data
warehouse.
A
fundamental challenge
... 8.
Multimedia
data
mining, including
text
mining, image mining,
and Web
min-
ing,
is
dealt
with
in
Chapter
9.
Finally,
certain
aspects
of
Bioinformatics,
as
an
application
of
data
mining,
...
... Introduction
to
Data
Mining
1
1.1
Introduction
1
1.2
Knowledge Discovery
and
Data Mining
5
1.3
Data Compression
10
1.4
Information Retrieval
12
1.5
Text Mining
14
1.6 Web
Mining
15
1.7
... actual
data
for
mining.
This also increases
the
mining
efficiency
by
reducing
the
time required
for
mining
the
preprocessed
data.
Data
preprocess-
ing
involves
data
cleaning, data transformation, ... multimedia
data
exploration,
data
mining should
no
longer
be
restricted
to the
mining
of
knowledge
from
large volumes
of
high-dimensional
datasets
in
traditional
databases
only.
...
... Implementing a DataMining Process Using Office 2007 187
Introducing the DataMining Client 188
Importing Data Using the DataMining Client 189
Data Exploration and Preparation 190
Discretizing Data with ... Data
Mining 413
Mining Aggregated Data 414
OLAP Pattern Discovery Needs 415
OLAP Mining versus Relational Mining 415
Building OLAP Mining Models Using Wizards and Editors 417
Using the DataMining ... 584
Exploring New DataMining Frontiers and Opportunities 585
Further Reference 586
Microsoft DataMining 586
General DataMining 586
Appendix A: Data Sets 589
MovieClick Data Set 589
Voting Records Data...