'Distinct values' presentation slideshows

Querying and Mining Data Streams: You Only Get One Look A Tutorial

Querying and Mining Data Streams: You Only Get One Look A Tutorial. Minos Garofalakis Johannes Gehrke Rajeev Rastogi Bell Laboratories Cornell University. Outline. Introduction & Motivation Stream computation model, Applications Basic stream synopses computation

1.4k views • 124 slides

SQL Unit 6 Views and Temporary Tables

SQL Unit 6 Views and Temporary Tables. Kirk Scott. 6.1 Introduction 6.2 Enabling Database Content in MS Access 6.3 Temporary Tables 6.4 Views 6.5 Inline Views 6.6 Details. 6.1 Introduction. It is possible to write relatively complex SQL queries.

950 views • 74 slides

Towards a Synopsis Warehouse

Towards a Synopsis Warehouse. Peter J. Haas IBM Almaden Research Center San Jose, CA. Acknowledgements:. Kevin Beyer Paul Brown Rainer Gemulla (TU Dresden) Wolfgang Lehner (TU Dresden) Berthold Reinwald Yannis Sismanis. Search. Business Intelligence. Enterprise Repository. Content

559 views • 45 slides

QC Your RDBMS Data Using Dictionary Tables

QC Your RDBMS Data Using Dictionary Tables. Harry Droogendyk Stratia Consulting Inc. QC Data. ETL process data summarization test data creation verifying data is a good thing!. QC Data. rudimentary data QC continuous numeric variables eg. weight, balance

544 views • 38 slides

Mickey Mouse does not live on Main Street USA

459 views • 35 slides

Data Mining

487 views • 33 slides

Algorithms for massive data sets

Algorithms for massive data sets. Lecture 2 (Mar 14, 2004) Yossi Matias & Ely Porat (partially based on various presentations & notes). Negative Result for Sampling [ Charikar, Chaudhuri, Motwani, Narasayya 2000 ].

391 views • 31 slides

A New Nonparametric Bayesian Model for Genetic Recombination in Open Ancestral Space

A New Nonparametric Bayesian Model for Genetic Recombination in Open Ancestral Space. Paper by E. P. Xing and K-A. Sohn. Presented by Chunping Wang Machine Learning Group, Duke University February 26, 2007. Outline. Terminology and Introduction

329 views • 22 slides

Discrete Random Variables

Discrete Random Variables. : 9 10 11 12. Numerical Outcomes. Consider associating a numerical value with each sample point in a sample space. (1,1) (1,2) (1,3) (1,4) (1,5) (1,6) (2,1) (2,2) (2,3) (2,4) (2,5) (2,6) (3,1) (3,2) (3,3) (3,4) (3,5) (3,6)

347 views • 21 slides

ITFN 2601 Introduction to Operating Systems

ITFN 2601 Introduction to Operating Systems. Lecture 23 Intro to Multimedia MMOS: Scheduling. Agenda. Intro to Multimedia Audio Video Multimedia Scheduling Round Robin General Real-time Rate Monotonic Earliest Deadline First. Intro to Multimedia.

330 views • 21 slides

Bayesian Generalized Kernel Mixed Models

Bayesian Generalized Kernel Mixed Models. Zhihua Zhang, Guang Dai and Michael I. Jordan JMLR 2011. Summary of contributions.

304 views • 19 slides

Reducing Symmetry in Matrix Models

Reducing Symmetry in Matrix Models. Alan Frisch, Ian Miguel, Toby Walsh (York) Pierre Flener, Brahim Hnich, Zeynep Kiziltan, Justin Pearson (Uppsala). Week 1. Week 2. Week 3. Week 4. Week 5. Week 6. Week 7. Period 1. 0 vs 1. 0 vs 2. 4 vs 7. 3 vs 6. 3 vs 7. 1 vs 5. 2 vs 4.

241 views • 15 slides

DISCRETE & RANDOM VARIABLES

DISCRETE & RANDOM VARIABLES. Discrete random variable. A discrete random variable is one which may take on only a countable number of distinct values such as 0, 1, 2, 3, 4, ...

390 views • 14 slides

Dialogue Act Tagging Using TBL

CISC 889: Statistical Approaches to NLP Spring 2003. Dialogue Act Tagging Using TBL. Sachin Kamboj. August 8, 2014. Outline. Dialogue Acts Transformation Based Learning (TBL) Introduction Training Phase Example Motivation for use of TBL in Dialogue Limitations of TBL

334 views • 13 slides

Data Preprocessing

Data Preprocessing. Lecture 12: Overview of data preprocessing Lecture 13: Descriptive data summarization Lecture 14: Data cleaning Lecture 15: Data integration/transformation and data reduction Lecture 16: Discretization and concept hierarchy generation and summary. Discretization.

234 views • 12 slides

Chapter 5 Query Optimization

Chapter 5 Query Optimization. indexes. For a MyISAM table, the table's data rows are kept in a data file, and index values are kept in an index file.

178 views • 12 slides

Data Preprocessing

Data Preprocessing. Lecture 12: Overview of data preprocessing Lecture 13: Descriptive data summarization Lecture 14: Data cleaning Lecture 15: Data integration/transformation and data reduction Lecture 16: Discretization and concept hierarchy generation and summary. Discretization.

309 views • 12 slides

Random Variables

646 views • 11 slides

Photograph, drawing, diagram, or graph supporting the headline assertion

188 views • 9 slides

Collection/Item Metadata Relationships

Collection/Item Metadata Relationships. Karen M. Wickett Richard J. Urban, Larry Jackson, Allen H. Renear Center for Informatics Research in Science and Scholarship Graduate School of Library and Information Science University of Illinois at Urbana-Champaign

202 views • 6 slides