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Data Mining Tutorial.21-40页翻译下载
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2019-07-03 10:00:20
Data Mining Tutorial.21-40页翻译
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Data Mining Tutorial.21-40页翻译下载
Data Mining Tutorial.21-40页翻译 相关下载链接://download.csdn.net/download/suncuckoo/2786825?utm_source=bbsseo
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Data
Min
ing
Tu
tor
ial
.
21
-
40
页
翻译
Data
Min
ing
Tu
tor
ial
.
21
-
40
页
翻译
Data
Min
ing
: A
Tu
tor
ial
-Based Primer, Second Edition
Data
Min
ing
: A
Tu
tor
ial
-Based Primer, Second Edition (Chapman & Hall/CRC
Data
Min
ing
and Knowledge Discovery Series) by Richard J. Roiger 2016 | ISBN: 1498763979 | English | 529 pages | True PDF | 32 MB "Dr. Roiger does an excellent job of describ
ing
in step by step detail formulae involved in various
data
min
ing
algorithms, along with illustrations. In addition, his
tu
tor
ial
s in Weka software provide excellent ground
ing
for s
tu
dents in comprehend
ing
the underpinn
ing
s of Machine Learn
ing
as applied to
Data
Min
ing
. The inclusion of Rapid
Min
er software
tu
tor
ial
s and examples in the book is also a definite plus since it is one of the most popular
Data
Min
ing
software platforms in use today." –Robert Hughes, Golden Gate University, San Francisco, CA, USA
Data
Min
ing
: A
Tu
tor
ial
-Based Primer, Second Edition provides a comprehensive introduction to
data
min
ing
with a focus on model build
ing
and test
ing
, as well as on interpret
ing
and validat
ing
results. The text guides s
tu
dents to understand how
data
min
ing
can be employed to solve real problems and recognize whether a
data
min
ing
solution is a feasible alternative for a specific problem. Fundamental
data
min
ing
strategies, techniques, and evaluation methods are presented and implemented with the help of two well-known software tools. Several new topics have been added to the second edition includ
ing
an introduction to Big
Data
and
data
analytics, ROC curves, Pareto lift charts, methods for handl
ing
large-sized, stream
ing
and imbalanced
data
, support vec
tor
machines, and extended coverage of tex
tu
al
data
min
ing
. The second edition contains
tu
tor
ial
s for attribute selection, deal
ing
with imbalanced
data
, outlier analysis, time series analysis,
min
ing
tex
tu
al
data
, and more. The text provides in-depth coverage of Rapid
Min
er S
tu
dio and Weka’s Explorer interface. Both software tools are used for stepp
ing
s
tu
dents through the
tu
tor
ial
s depict
ing
the knowledge discovery process. This allows the reader maximum flexibility for their hands-on
data
min
ing
experience.
CityEngine案例系列(
Tu
tor
ial
_15_Publish_WebScenes)
本课程适用于cityengine爱好者,游戏开发者。详细介绍cityengine发布场景的方法,及其3ws文件通过http://www.eyearth.com/mapdateviewer.html 浏览场景的方法。
Encyclopedia of Machine Learn
ing
and
Data
Min
ing
2nd.Edition.pdf
This authoritative, expanded and updated second edition of Encyclopedia of Machine Learn
ing
and
Data
Min
ing
provides easy access to core information for those seek
ing
entry into any aspect within the broad field of Machine Learn
ing
and
Data
Min
ing
. A paramount work, its 800 entries - about 150 of them newly updated or added - are filled with valuable litera
tu
re references, provid
ing
the reader with a portal to more detailed information on any given topic. Topics for the Encyclopedia of Machine Learn
ing
and
Data
Min
ing
include Learn
ing
and Logic,
Data
Min
ing
, Applications, Text
Min
ing
, Statistical Learn
ing
, Reinforcement Learn
ing
, Pattern
Min
ing
, Graph
Min
ing
, Relational
Min
ing
, Evolutionary Computation, Information Theory, Behavior Clon
ing
, and many others. Topics were selected by a dist
ing
uished international advisory board. Each peer-reviewed, highly-struc
tu
red entry includes a definition, key words, an illustration, applications, a bibliography, and links to related litera
tu
re. The entries are exposi
tor
y and
tu
tor
ial
, mak
ing
this reference a practical resource for s
tu
dents, academics, or professionals who employ machine learn
ing
and
data
min
ing
methods in their projects. Machine learn
ing
and
data
min
ing
techniques have countless applications, includ
ing
data
science applications, and this reference is essent
ial
for anyone seek
ing
quick access to vital information on the topic.
oracle
data
min
ing
tu
tor
ial
oracle
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tu
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