the voice and data communications handbook fourth edition
data structures and algorithms in java fourth edition
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28/04/2014, 15:41
... Tamassia
Preface to the Fourth Edition
This fourth edition is designed to provide an introduction to data structures and
algorithms, including their design, analysis, and implementation. In ... contributed to the development of the Java
code examples in this book and to the initial design, implementation, and testing of
the net.datastructures library of data structures and algorithms ... Vesselin Arnaudov and ike Shim for testing the current version of
net.datastructures
Many students and instructors have used the two previous editions of this book and
their experiences and responses...
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Data Mining and Knowledge Discovery Handbook, 2 Edition part 130 doc
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04/07/2014, 05:21
... know the
data is is a very important part of Data Mining, and many data visualization facilities and data
preprocessing tools are provided. All algorithms and methods take their input in the form ... of
the data, to retrieve the exact record underlying a particular data point, and so on.
The Explorer interface does not allow for incremental learning, because the Preprocess
panel loads the dataset ... specified.
Explanations of these options and their legal values are available as built-in help in the graphi-
cal user interfaces. They can also be listed from the command line. Additional information and
pointers...
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Data Mining and Knowledge Discovery Handbook, 2 Edition part 1 pps
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... enterprises. Thus, we have first hand experience in the needs
of the KDD/DM community in research and practice. This handbook evolved from
these experiences.
The first edition of the handbook, which was published ... include the new advances in
the field in a second edition of the handbook. About half of the book is new in this
edition. This second edition aims to refresh the previous material in the fundamental
areas, ... abundance of data.
Knowledge Discovery in Databases (KDD) is the process of identifying valid,
novel, useful, and understandable patterns from large datasets. Data Mining (DM)
is the mathematical...
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Data Mining and Knowledge Discovery Handbook, 2 Edition part 2 pptx
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04/07/2014, 05:21
... Multimedia Data Mining
58 Data Mining in Medicine
Nada Lavra
ˇ
c, Bla
ˇ
z Zupan 1111
59 Learning Information Patterns in Biological Databases - Stochastic
Data Mining
Gautam B. Singh 1137
60 Data Mining ... Kovalerchuk, Evgenii Vityaev 1153
61 Data Mining for Intrusion Detection
Anoop Singhal, Sushil Jajodia 1171
62 Data Mining for CRM
Kurt Thearling 1181
63 Data Mining for Target Marketing
Nissan ... Rokach 959
51 Data Mining using Decomposition Methods
Lior Rokach, Oded Maimon 981
52 Information Fusion - Methods and Aggregation Operators
Vicenc¸ Torra 999
53 Parallel And Grid-Based Data Mining...
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Data Mining and Knowledge Discovery Handbook, 2 Edition part 3 pptx
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04/07/2014, 05:21
... does the understanding and the automation of the nine steps
and their interrelation. For this to happen we need better characterization of the KDD
problem spectrum and definition. The terms KDD and ... unknown
patterns. The model is used for understanding phenomena from the data, analysis
and prediction.
The accessibility and abundance of data today makes Knowledge Discovery and
Data Mining a matter ... DM Trends 6. The Organization of the Handbook 7. New to
This Edition
The special recent aspects of data availability that are promoting the rapid develop-
ment of KDD and DM are the electronically...
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Data Mining and Knowledge Discovery Handbook, 2 Edition part 4 ppsx
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04/07/2014, 05:21
... tools and techniques,
Morgan Kaufmann Pub, 2005.
Wu, X. and Kumar, V. and Ross Quinlan, J. and Ghosh, J. and Yang, Q. and Motoda, H. and
McLachlan, G.J. and Ng, A. and Liu, B. and Yu, P.S. and others, ... (Steps 3, 4 of the KDD process). The
Data Mining methods are presented in the second part with the introduction and
the very often-used supervised methods. The third part of the handbook considers
Part ... of the two emerging areas: mul-
timedia and data mining. Instead, the multimedia data mining research focuses
on the theme of merging multimedia and data mining research together to exploit
the...
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Data Mining and Knowledge Discovery Handbook, 2 Edition part 5 pptx
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04/07/2014, 05:21
... large data sets has
given rise to the fields of Data Mining (DM) and data warehousing (DW). Without
clean and correct data the usefulness of Data Mining and data warehousing is mit-
igated. Thus, data ... (Galhardas, 2001) data cleansing is the process of eliminating the errors and the
inconsistencies in data and solving the object identity problem. Hernandez and Stolfo
(1998) define the data cleansing ... attract the attention of the researchers and
practitioners in the field. It is the first step in defining and understanding the data
cleansing process.
There is no commonly agreed formal definition of data...
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Data Mining and Knowledge Discovery Handbook, 2 Edition part 6 ppt
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04/07/2014, 05:21
... on Data Warehousing
and Knowledge Discovery; 2002 September 04-06; 170-180.
Hernandez, M. & Stolfo, S. Real-world Data is Dirty: Data Cleansing and The Merge/Purge
Problem, Data Mining and ... (Brazdil and Bruha,
1992) and (Bruha, 2004)
30 Jonathan I. Maletic and Andrian Marcus
Ballou, D. P. & Tayi, G. K. Enhancing Data Quality in Data Warehouse Environments, Com-
munications of the ... that the attribute value was not
placed into the table because it was forgotten or it was placed into the table but later
O. Maimon, L. Rokach (eds.), Data Mining and Knowledge Discovery Handbook, ...
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Data Mining and Knowledge Discovery Handbook, 2 Edition part 7 ppsx
Ngày tải lên :
04/07/2014, 05:21
... y
i
,
1ifx and y are symbolic and x
i
= y
i
,
or x
i
=?ory
i
=?,
|x
i
−y
i
|
r
if x
i
and y
i
are numbers and x
i
= y
i
,
where r is the difference between the maximum and minimum of the known ... method. The difference is that the
original data set, containing missing attribute values, is first split into smaller data
sets, each smaller data set corresponds to a concept from the original data ... smaller data set is constructed from one of the original concepts, by
restricting cases to the concept. For the data set from Table 3.7, two smaller data sets
are created, presented in Tables 3.12 and...
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Data Mining and Knowledge Discovery Handbook, 2 Edition part 8 potx
Ngày tải lên :
04/07/2014, 05:21
... variance of the projection of the data along n is just
λ
1
.
The above construction captures the variance of the data along the direction n.
To characterize the remaining variance of the data, let’s ... of
the direction we choose. If the distance along the projection is parameterized by
ξ
≡ cos
θ
, where
θ
is the angle between I and the line from the origin to a point
on the sphere, then the ... If the
data is not centered, then the mean should be subtracted first, the dimensional reduc-
tion performed, and the mean then added back
7
; thus in this case, the dimensionally
reduced data...
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Data Mining and Knowledge Discovery Handbook, 2 Edition part 9 pdf
Ngày tải lên :
04/07/2014, 05:21
... or
video data) and to make the features more robust. The above features, computed by
taking projections along the n’s, are first translated and normalized so that the signal
data has zero mean and the ... 1,···,n, there is a single variable g such
that the correlation between x
i
and x
j
vanishes for i = j given the value of g, then g is
the underlying ’factor’ and the off-diagonal elements of the ... right hand side where d m and d > r, and ap-
proximate the eigenvector of the full kernel matrix K
mm
by evaluating the left hand
rows (and hence columns) are linearly independent, and suppose...
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Data Mining and Knowledge Discovery Handbook, 2 Edition part 10 ppt
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... j=1
D
ij
e
k
The first term in the square brackets is the vector of squared distances from the test
point to the landmarks, f. The third term is the row mean of the landmark distance
squared matrix,
¯
E. The ... of arcs, the cut is defined as
the sum of the weights of the removed arcs. Given the mapping of data to graph de-
fined above, a cut defines a split of the data into two clusters, and the minimum ... eigenvalues is equal to the
number of connected components in the graph, and in fact the spectrum of a graph is
the union of the spectra of its connected components; and the sum of the eigenvalues
is...
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Data Mining and Knowledge Discovery Handbook, 2 Edition part 11 pdf
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04/07/2014, 05:21
... required for the algorithm to run, and the
size of the data set. When discussing dimension reduction, given a set of records,
the size of the data set is defined as the number of attributes, and is ... particular, the model may be a classification model). The cost
is a function of the theoretical complexity of the Data Mining algorithm that derives
the model, and is correlated with the time required ... instances
the inconsistency count is the number of instances in the group minus the number of
instances in the group with the most frequent class value. The overall inconsistency
rate is the sum of the...
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Data Mining and Knowledge Discovery Handbook, 2 Edition part 12 ppsx
Ngày tải lên :
04/07/2014, 05:21
... dependent on the values of other features and the class,
and as such, provide further information about the class. On the other hand, redun-
dant features, are those whose values are dependent on the ... and
orthogonal to the first PC, and so on. There are as many PCs as the number of the
original variables. For many datasets, the first several PCs explain most of the vari-
ance, so that the rest can ... dimension of the data by finding a few
orthogonal linear combinations (the PCs) of the original variables with the largest
variance. The first PC, s
1
, is the linear combination with the largest...
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Data Mining and Knowledge Discovery Handbook, 2 Edition part 13 pot
Ngày tải lên :
04/07/2014, 05:21
... the smallest. If
the consistency of the dataset after the merge is above a given threshold, the merge
is performed. Otherwise this pair of intervals are marked as non-mergable and the
next candidate ... each division, the resulting information gain of the data is calculated. The
attribute that obtains the maximum information gain is chosen to be the current tree
node. And the data are divided ... that
exhibit the greatest similarity between each other. The cluster formation continues as
long as the level of consistency of the partition is not less than the level of consistency
of the original data. ...
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