data mining teaching experience at the fib. what is data mining? a broad set of techniques and...

10

Data Mining Teaching experience at the FIB

Upload: lee-riley

Post on 02-Jan-2016

218 views

Category:

Documents

1 download

Report

Download

Embed Size (px):

TRANSCRIPT

Page 1: Data Mining Teaching experience at the FIB. What is Data Mining? A broad set of techniques and algorithms brought from machine learning and statistics

Data Mining

Teaching experience at the FIB

Page 2: Data Mining Teaching experience at the FIB. What is Data Mining? A broad set of techniques and algorithms brought from machine learning and statistics

What is Data Mining?

A broad set of techniques and algorithms brought from machine learning and statistics to make decisions based on data … plus a lot of experience and common sense

Page 3: Data Mining Teaching experience at the FIB. What is Data Mining? A broad set of techniques and algorithms brought from machine learning and statistics

What subset is taught at the FIB?

Introduction to DM Multivariate statistics Clustering Association rules Regression and GLMs Decision trees Bayesian gaussian classifiers Nearest neighbours Neural networks Support vector machines

Page 4: Data Mining Teaching experience at the FIB. What is Data Mining? A broad set of techniques and algorithms brought from machine learning and statistics

Additional subjects

Feature selection and extraction Model evaluation, selection and combination Data mining in the real world ….

– Does it need professional software?– A talk by a professional

Page 5: Data Mining Teaching experience at the FIB. What is Data Mining? A broad set of techniques and algorithms brought from machine learning and statistics

Practical side

No exam Three practical homeworks:

– 1. Multivariate statistics (15%)– 2. Clustering & association rules (15%)– 3. Full Data Mining Project (70%)

Involves a 20’ oral defense!

Lab sessions (2 hours/week) Language selected: R

Page 6: Data Mining Teaching experience at the FIB. What is Data Mining? A broad set of techniques and algorithms brought from machine learning and statistics

Now for the funny part …

Why two teachers?– One from Software department (a computer

scientist)– One from Statistics department (a statistician)

Page 7: Data Mining Teaching experience at the FIB. What is Data Mining? A broad set of techniques and algorithms brought from machine learning and statistics

An equivalence table

Page 8: Data Mining Teaching experience at the FIB. What is Data Mining? A broad set of techniques and algorithms brought from machine learning and statistics

Some tips for the students

A successful data mining project has four components:

1. Good data2. Clean goals3. Good algorithms4. Human expertise

Page 9: Data Mining Teaching experience at the FIB. What is Data Mining? A broad set of techniques and algorithms brought from machine learning and statistics

The students’ replies (and subtext)

R is not a programming language– (it can’t be programmed as if C)

The results are not as good as we expected– (although we are very clever)

Too much theory– (but later on, we shall be missing it)

All in all, we have enjoyed it– (?)

Page 10: Data Mining Teaching experience at the FIB. What is Data Mining? A broad set of techniques and algorithms brought from machine learning and statistics

In conclusion

The students like the course, specially the practical work

They tend to work autonomously, but not always for the good

In the end, no two results are identical This is a course with much room to improve

on the teacher’s part

Data Mining Lecture 1: Introduction to Data Mining

© Jayzed Data Models Inc. 1999-2020 - fib-dm.com€¦ · FIB-DM Data Model ROBMS RDF Data OWL xso XML Message Process Level FIB-UM Enterprise Department Project Object Ontology Extract

Introduction to Introduction to Data Mining Data Mining

Massive Data Analytics Data Mining Introductiondisi.unitn.it/.../MassiveDataAnalytics/slides/DataMiningIntro-2in1.pdfMassive Data Analytics Data Mining Introduction ... Data mining,

Financial Industry Business Data Model (FIB-DM) …...conceptual data model in sync with FIB-DM. Indeed, just like we derive a Physical Data Model (PDM) from a Logical Data Model (LDM),

Introduction to Data Mining - homepages.math.uic.eduhomepages.math.uic.edu/~jyang06/stat486/R/DataMining_JYang2014.pdfFundamentals of Data Mining Typical Data Mining Tasks Data Mining

1 Chapter 1. Introduction Motivation: Why data mining? What is data mining? Data Mining: On what kind of data? Data mining functionality Major issues in

Applied Data Mining - Lagout Mining/Applied Data Mining [Xu... · The book reviews applied data mining from theoretical basis to ... data mining application arenas, ... research topics

CS590D: Data Mining Chris Clifton - Purdue University · Data Mining: Classification Schemes • General functionality – Descriptive data mining – Predictive data mining ... –

Data Mining-Graph Mining

Fibonacci fib(n) fib(n-1) fib(n-2) fib(n-2) fib(n-3) fib(n-3) fib(n-4) …galles/cs673/lecture/lecture9... · 2016-09-19 · •First, ﬁll in the “base cases” of the recursion

September 4, 20151 Chapter 1. Introduction Motivation: Why data mining? What is data mining? Data Mining: On what kind of data? Data mining functionality

Course : Data mining - Lecture : Mining data streams

Data Mining - The opportunity lies with Data!Data mining

Enhancing Fairness of FIB Lookup in Named Data Networking

Data Mining BY JEMINI ISLAM. Data Mining Outline: What is data mining? Why use data mining? How does data mining work The process of data mining Tools

Data Mining vs. Statistics Pavel Brusilovsky. 2 Objectives 2 Intro to Data Mining Data Mining vs. Statistics Data Mining vs. Text Mining Applications

Lecture 2: Data Mining 1. Roadmap What is data mining? Data Mining Tasks – Classification/Decision Tree – Clustering – Association Mining Data Mining

Data Mining LECTURE # 01 Introduction to Data Mining

October 18, 2015 Data Mining: Concepts and Techniques 1 DATA MINING Motivation: Why data mining? What is data mining? Data Mining: On what kind of data?

1 Data Mining Chapter 26. 2 Chapter 1. Introduction Motivation: Why data mining? What is data mining? Data Mining: On what kind of data? Data mining functionality

Data Mining and Applications - antoniomucherino.it · Data Mining and Applications Data Mining Why Data Mining? Introduction to Data Mining Example III - text mining Let us suppose

Data Mining By: Thai Hoa Nguyen Pham. Data Mining Define Data Mining Classification Association Clustering

Data Mining Introduction to Data Mining

Introduction to Algorithmic Complexity · Fib(3) = 3, 0.00 msec Fib(4) = 5, 0.00 msec Fib(5) = 8, 0.00 msec Fib(6) = 13, 0.00 msec Fib(7) = 21, 0.00 msec Fib(8) = 34, 0.00 msec Fib(9)

UNIT - I Data Mining. UNIT - I Introduction : Fundamentals of data mining, Data Mining Functionalities, Classification of Data Mining systems, Major issues

Introduction to Data Mining and Knowledge Discovery · PDF fileIntroduction to Data Mining and ... Introduction to Data Mining and Knowledge Discovery, ... Data mining and data warehousing

Mining Unstructured Data (Text Data Mining) - Chapters Site IIA Nov5...Mining Unstructured Data (Text Data Mining) ... Text Mining tools and tips for beginning to use text ... free

DATA MINING AND ANALYSIS - doc.lagout.org Mining/Data Mining and Analysis... · DATA MINING AND ANALYSIS The fundamental algorithms in data mining and analysis form the basis

Data Mining Chapter 1 Introduction -- Basic Data Mining Tasks -- Related Concepts -- Data Mining Techniques

Data Mining: What is Data Mining?

DATA MINING WITH - Lagout Mining/Data Mining with Decision... · Library of Congress Cataloging-in-Publication Data Rokach, Lior. Data mining with ... Data mining is the science,

Data Mining für Business Intelligence Data Mining for

Data mining week 1 - pengantar data mining

Secure Data Processing - uni-leipzig.de · PRIVACY-PRESERVING DATA MINING 12 Local Data Local Data Local Data Warehouse Data Mining Local Data Mining Local Data Mining Combiner Local