'Classification problem' diaporamas de présentation

Ling 570 Day 7: Classifiers

Ling 570 Day 7: Classifiers. Outline. Open questions One last bit on POS taggers: Evaluation Classifiers!. Evaluating Taggers. Evaluation. How can we evaluate a POS tagger?. Evaluation. How can we evaluate a POS tagger? Overall error rate w.r.t . gold-standard test set.

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The Case for A Data Mining Approach to Technical Analysis

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Data Mining and Machine Learning via Support Vector Machines

Data Mining and Machine Learning via Support Vector Machines. Dave Musicant. Graphic generated with Lucent Technologies Demonstration 2-D Pattern Recognition Applet at http://svm.research.bell-labs.com/SVT/SVMsvt.html. Outline. The Supervised Learning Classification Problem

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Malicious Code Detection and Security Applications

Malicious Code Detection and Security Applications. Prof. Bhavani Thuraisingham The University of Texas at Dallas. October 2008. Information Harvesting. Knowledge Mining. Data Mining. Knowledge Discovery in Databases. Data Dredging. Data Archaeology.

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Support Vector Machines

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Improving Software Reliability via Static and Dynamic Analysis

Improving Software Reliability via Static and Dynamic Analysis. Group Overview. Inputs: Current funding support NSF CyberTrust (3 yrs), NSF SoD (3 yrs), ARO (3 yrs), NIST supplement, IBM Faculty Award, Microsoft Research, ABB Research Collaboration with agencies and industry

565 views • 36 slides

Understanding Temporal Intent of User Query based on Time-based Query Classification

Understanding Temporal Intent of User Query based on Time-based Query Classification. Pengjie Ren, Zhumin Chen and Jun Ma Information Retrieval Lab. Shandong University ??????? 2013 ? 11 ? 18 ?. Outline. Why Temporal Intent Detection? Query Temporal Pattern Taxonomy

494 views • 31 slides

Strategy-Proof Classification

Strategy-Proof Classification. Reshef Meir School of Computer Science and Engineering, Hebrew University. A joint work with Ariel. D. Procaccia and Jeffrey S. Rosenschein. Strategy-Proof Classification . Introduction Learning and Classification An Example of Strategic Behavior

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Wall-Corner Classification. A New Ultrasonic Amplitude Based Approach

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Latent Semantic Indexing for the Routing Problem

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A Role of Dialogue Strategy in Multiattribute Classification Performance

A Role of Dialogue Strategy in Multiattribute Classification Performance. Eugenia Furems Institute for System Analysis of Russian Academy of Sciences fem@mail.ru. A Role of Dialogue Strategy in Multiattribute Classification Performance Outline.

448 views • 26 slides

TagLearner: A P2P Classifier Learning System from Collaboratively Tagged Text Documents

TagLearner: A P2P Classifier Learning System from Collaboratively Tagged Text Documents. Haimonti Dutta 1 , Xianshu Zhu 2 , Tushar Muhale 2 , Hillol Kargupta 2 , Kirk Borne 3 , Codrina Lauth 4 , Florian Holz 5 , and Gerherd Heyer 5. 1 Columbia University

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Opinion Mining in GATE Horacio Saggion & Adam Funk

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Opinion Mining in GATE Horacio Saggion & Adam Funk

382 views • 18 slides

Using Support Vector Machine for Integrating Catalogs

Using Support Vector Machine for Integrating Catalogs. Ping-Tsun Chang Intelligent Systems Laboratory NTU/CSIE. Integrating Catalogs. Key Insight

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Active Learning in Text Retrieval

Active Learning in Text Retrieval. Introduction. Passive Learning vs. Active Learning Active Learning: Intelligently choose good questions to reach high performance using as few examples as possible. Learning conjunctions. Protocol I: teacher proposes questions to learner

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2D1431 Machine Learning

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Age of Abalones using Physical Characteristics: A Classification Problem

Age of Abalones using Physical Characteristics: A Classification Problem. Hiran Mayukh ECE 539. What is an Abalone?. S ea snails found worldwide Also called sea-ears and ear-shells. What is this project about? . Finding age of an abalone Cumbersome laboratory process

443 views • 9 slides