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Syllabus 2013-14 - 13312023 - Data Mining (Minería de datos)
- Level 1: Tutorial support sessions, materials and exams in this language
- Level 2: Tutorial support sessions, materials, exams and seminars in this language
- Level 3: Tutorial support sessions, materials, exams, seminars and regular lectures in this language
DEGREE: | Grado en Ingeniería informática |
FACULTY: | SCHOOL OF ENGINEERING OF JAÉN |
ACADEMIC YEAR: | 2013-14 |
COURSE: | Data Mining |
NAME: Data Mining | |||||
CODE: 13312023 | ACADEMIC YEAR: 2013-14 | ||||
LANGUAGE: English | LEVEL: 2 | ||||
ECTS CREDITS: 6.0 | YEAR: 4 | SEMESTER: PC |
NAME: JESÚS DÍAZ, MARÍA JOSÉ DEL | ||
DEPARTMENT: U118 - INFORMÁTICA | ||
FIELD OF STUDY: 075 - CIENCIA DE LA COMPUTACIÓN E INT. ARTIFICIAL | ||
OFFICE NO.: A3 - 131 | E-MAIL: mjjesus@ujaen.es | P: 953212444 |
WEBSITE: - | ||
ORCID: https://orcid.org/0000-0002-7891-3059 | ||
LANGUAGE: English | LEVEL: 2 |
I. Introduction to Data Mining
1.
E
xtracting knowledge
in large
databases.
Data Mining
.
Applications.
II. Data preparation
2
.
Data collection and
data preparation
3
.
Reduction
of dimensionality
4
.
Discretization
III. Predictive Data Mining
5
.
The classification problem
6
.
Classification
trees and
rules
6
.
Classification
with other techniques
7
.
Numerical prediction
or
regression
IV
.
Descriptive
Data Mining
9.
A
ssociation rules
10
. Subgroup discovery
VII. Evaluation, dissemination and use of models. Data
analysis tools.
11.
Evaluation
, dissemination and use
of models.
12.
Data
analysis tools
.
VII. New Trends in Data Mining
13. Business Intelligence and Big Data
The course
is divided into
two related parts
,
theory and
practice.
The theory
will be conducted primarily
through
master classes
,
including
activity sessions
to evaluate the
student's participation in
the course.
The practical part
will be held in
the computer lab
.
During
the academic year
objective
tests will be performed
to assess
the knowledge acquired
by the student.
Students with special educational needs should contact the Student Attention Service (Servicio de Atención y Ayudas al Estudiante) in order to receive the appropriate academic support
To
pass the course it will
needed to
pass both
the theoretical and
the
practical part
.
The theoretical part and participation
will be evaluated
with
objective tests
of theoretical concepts and
practical exercises
related to the subject
.
The
practical
part of
the delivery
will be assessed through
practical work
performed
by computer
, with the
the work relating
to seminars
and presentations
raised
and with the
report
associated with them
.
The
assessment
will be continuous
and incremental
to
evaluate both
the defense
end of each
work
and the evolution
of the student
during practices
.
The portion corresponding to
participation
will be evaluated
by
some
quizzes
conducted
during class hours
corresponding to
theory and practices.
- Practical applications of data mining [Recurso electrónico]. Edition: -. Author: Suh, Sang C. Publisher: Sudbury, Mass. : Jones & Bartlett Learning, c2012 (Library)
- Data mining : concepts and techniques. Edition: 3rd ed. Author: Han, Jiawei. Publisher: Burlington, MA : Elsevier, c2012 (Library)
- Data mining: practical machine learning tools and techniques. Edition: 3rd ed.. Author: Witten, Ian H.. Publisher: Amsterdam: Morgan Kaufman: Elsevier, 2011 (Library)
- Data mining [Recurso electrónico] : practical machine learning tools and techniques. Edition: 3rd ed. Author: Witten, I. H. (Ian H.). Publisher: Burlington, MA : Morgan Kaufmann Publishers, 2011 (Library)
- Data mining techniques for marketing, sales and customer relationship management. Edition: 3rd ed.. Author: Linoff, Gordon S. Publisher: New York, NY [etc.] : Wiley, 2011 (Library)
- Data preparation for data minig. Edition: -. Author: Pyle, Dorian. Publisher: San Francisco: Morman Kaufmann, 1999 (Library)
- Predictive data mining : a practical guide. Edition: -. Author: Weiss, Sholom M.. Publisher: San Francisco: Morgan Kaufmann Publishers, cop. 1998 (Library)