'Classification model' diaporamas de présentation

Object Segmentation

869 views • 72 slides

Agenda

Agenda. Overview Why TransCAD Challenges/tips Initiatives Applications. Overview. Transportation planning and policy guidance 3 C process Planning tools Travel demand modeling Project level forecasts. Role of Statewide Planning. Organizational Structure.

1.04k views • 65 slides

Data Mining: A Closer Look

Data Mining: A Closer Look. Chapter 2. 2.1 Data Mining Strategies (p35). Moh!. Classification. Learning is supervised. The dependent variable is categorical. Well-defined classes. Current rather than future behavior. Estimation. Learning is supervised.

570 views • 42 slides

Special Topics in Text Mining

514 views • 42 slides

Recognizing Human Actions by Attributes

Recognizing Human Actions by Attributes. CVPR2011 Jingen Liu, Benjamin Kuipers , Silvio Savarese Dept. of Electrical Engineering and Computer Science University of Michigan. Outline. Introduction Our Contributions Attribute-Based Action Representation Learning Data-Driven Attributes

586 views • 41 slides

Artificial Neural Networks and Data Mining

840 views • 39 slides

System models

System models. Abstract descriptions of systems whose requirements are being analysed. Objectives. To explain why the context of a system should be modelled as part of the RE process To describe behavioural modelling, data modelling and object modelling

524 views • 39 slides

UNIT 1 Foundations

525 views • 36 slides

Oracle Data Mining and Epidemiological Analysis

Oracle Data Mining and Epidemiological Analysis. Scott A. Rappoport, OCP MTS Technologies OracleWorld 2003 San Francisco, CA. Presentation Goals. Short intros Vocabulary Present Basic Medical Terms Describe Data Mining Models and Terms Synthesize What questions are we asking?

559 views • 36 slides

Learning to Extract Cross-Session Search Tasks

Learning to Extract Cross-Session Search Tasks. Hongning Wang 1 , Yang Song 2 , Ming-Wei Chang 2 , Xiaodong He 2 , Ryen W. White 2 and Wei Chu 3. 2 Microsoft Research, Redmond WA 3 Microsoft Bing, Bellevue WA, 98004 USA { yangsong,minchang,xiaohe,ryenw,wechu }@ microsoft.com.

412 views • 32 slides

Learning to Extract Cross-Session Search Tasks

Learning to Extract Cross-Session Search Tasks. Hongning Wang 1 , Yang Song 2 , Ming-Wei Chang 2 , Xiaodong He 2 , Ryen W. White 2 and Wei Chu 3. 2 Microsoft Research, Redmond WA 3 Microsoft Bing, Bellevue WA, 98004 USA { yangsong,minchang,xiaohe,ryenw,wechu }@ microsoft.com.

429 views • 32 slides

February 4, 2010

February 4, 2010 1. Do Not Try to Time the Market Flows to Equity Funds Related to Global Stock Price Performance Source: Investment Company Institute The Danger of Trying to Time the Market 15 Year Average Annual Returns (1994-2008) 15 Year Average Annual Return 6.5% 1.9% -3.7 %

717 views • 29 slides

Tanzania DPG

Tanzania DPG. Public Private Partnerships 16 January, 2013. What are Public-Private Partnerships?. A long-term (5 to 30 year) contract between a public entity and a private company to provide a public service : design; finance; build; maintain; and/or operate Output orientation

496 views • 27 slides

A Cross -Lingual ILP Solution to Zero Anaphora Resolution

481 views • 26 slides

CBSE: Research Results, Experiences and Challenges

CBSE: Research Results, Experiences and Challenges. Third WorkShop. Stefano De Panfilis Engineering Ingegneria Informatica S.p.A. 25-26 September 2003, Larnaca. Summary. CBSEnet the motivation / scenario CBSEnet the solution CBSEnet the project CBSEnet the current status

407 views • 25 slides

Lazy vs. Eager Learning

Lazy vs. Eager Learning. Lazy vs. eager learning Lazy learning (e.g., instance-based learning): Simply stores training data (or only minor processing) and waits until it is given a test tuple

3.93k views • 20 slides

STUDENT RESEARCH SYMPOSIUM 2005

343 views • 20 slides

An Ensemble-based Approach to Fast Classification of Multi-label Data Streams

An Ensemble-based Approach to Fast Classification of Multi-label Data Streams. Xiangnan Kong, Philip S. Yu. Dept. of Computer Science University of Illinois at Chicago. Introduction: Data Stream . Data Stream: high speed data flow continuously arriving, changing. Applications:

329 views • 20 slides

Laboratory of Analytical Chemistry, Nijmegen University

MV Scientific short echo time prototype Demo of most important features. Arjan Simonetti, Joshua Underwood, Willem Melssen, Geert Postma, Lutgarde Buydens. Laboratory of Analytical Chemistry, Nijmegen University. Main goals

251 views • 9 slides

Classification Model for Learning Outcomes of Training Evaluations

Classification Model for Learning Outcomes of Training Evaluations. Compilation Procedures Organisation. Verbal Knowledge Knowledge Organisation Cognitive Strategies. Attitude Motivation Goal Setting.

86 views • 1 slides