'Partition data' diaporamas de présentation

Chapter 2: Data Preprocessing

Chapter 2: Data Preprocessing. Why preprocess the data? Data cleaning Data integration and transformation Data reduction Discretization and concept hierarchy generation Summary. Data Reduction Strategies. Why data reduction? A database/data warehouse may store terabytes of data

1.7k views • 73 slides

Microsoft Research Jim Gray Researcher Microsoft Research Microsoft Corporation

Microsoft Research Jim Gray Researcher Microsoft Research Microsoft Corporation. Outline. Highlights of MS Research DB-Related Research in some detail. Microsoft Research http://Research.Microsoft.com/. Goal: pursue strategic technologies for MS 231 Researchers in 20 areas

515 views • 51 slides

Tutorial on Data Mining

Tutorial on Data Mining. Workshop of the Indian Database Research Community Sunita Sarawagi School of IT, IIT Bombay. Data mining. Process of semi-automatically analyzing large databases to find interesting and useful patterns

557 views • 43 slides

Time Series Forecasting With Feed-Forward Neural Networks: Guidelines And Limitations

Time Series Forecasting With Feed-Forward Neural Networks: Guidelines And Limitations. Eric Plummer Computer Science Department University of Wyoming March 13, 2014. Topics. Thesis Goals Time Series Forecasting Neural Networks K-Nearest-Neighbor Test-Bed Application Empirical Evaluation

707 views • 40 slides

Data Mining: Data Preparation

Data Mining: Data Preparation. Data Preprocessing. Why preprocess the data? Data cleaning Data integration and transformation Data reduction Discretization and concept hierarchy generation Summary. Why Data Preprocessing?. Data in the real world is dirty

636 views • 37 slides

Data Mining: Data Preparation

Data Mining: Data Preparation. Data Preprocessing. Why preprocess the data? Data cleaning Data integration and transformation Data reduction Discretization and concept hierarchy generation Summary. Why Data Preprocessing?. Data in the real world is dirty

931 views • 37 slides

One Torus to Rule Them All: Multi-dimensional Queries in P2P Systems

One Torus to Rule Them All: Multi-dimensional Queries in P2P Systems. Prasanna Ganesan Beverly Yang Hector Garcia-Molina Stanford University. Motivation. P2P Systems Dynamic set of nodes Dynamic data distributed over nodes No centralization

325 views • 21 slides

Minimum Spanning Tree

2.83k views • 19 slides

Chapter 27

Chapter 27. Data Mining Concepts. Overview of Data Mining Technology. Data Mining aka Knowledge Discovery in Databases (KDD) Discovery of new information in terms of patterns or rules from vast amounts of data Must be carried out efficiently on large files and databases. Goals of Data Mining.

192 views • 19 slides

Data Analysis II

Mingwei Lei March 3 rd , 2010 Econ 201S. Data Analysis II. Things to Improve on From Last Presentation. Explain everything on slides Include graphs as well as numerical results Improve the visual presentation of the slides More ideas for research. VZ: Tests Using TP Quarticity. Z TP

233 views • 13 slides