'Test set' presentation slideshows

Spatial and Temporal Data Mining

Spatial and Temporal Data Mining. Classification and Prediction. Vasileios Megalooikonomou. (based on notes by Jiawei Han and Micheline Kamber). Agenda. What is classification? What is prediction? Issues regarding classification and prediction Classification by decision tree induction

1.24k views • 92 slides

Classification: Basic Concepts and Decision Trees

Classification: Basic Concepts and Decision Trees. A programming task. Classification: Definition. Given a collection of records ( training set ) Each record contains a set of attributes , one of the attributes is the class .

1.17k views • 71 slides

CS 4705 Part of Speech Tagging

CS 4705 Part of Speech Tagging. Slides adapted from Bonnie Dorr, Julia Hirschberg, Dan Jurafsky, and James Martin. Outline. Finishing up Last time Evaluation Other Methods Transformation rule based Markov Chains. Evaluating performance. How do we know how well a tagger does?

718 views • 42 slides

WINNING SPIRIT RACING CAMPS IN YOUR OWN PO OL - SAMPLE FORMAT - CREATE YOUR OWN OFF MENU

515 views • 42 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

Improving Protein-Ligand Binding Affinity Prediction using Random Forest

Improving Protein-Ligand Binding Affinity Prediction using Random Forest. Hongjian Li Department of Computer Science and Engineering Chinese University of Hong Kong 1 April 2014 http :// istar.cse.cuhk.edu.hk JackyLeeHongJian@Gmail.com. Protein-Ligand Docking.

661 views • 38 slides

Model Evaluation, Validation and Testing

Model Evaluation, Validation and Testing. Lecture 17 Courtesy to Drs. . H. Witten, E. Frank and M. A. Hall. Outline. Issues : training, testing, tuning Predicting performance: confidence limits Holdout , cross-validation, bootstrap Comparing schemes: the t-test

539 views • 37 slides

My Life With Bugs, or, Why I Believe in Combinatorial Testing

My Life With Bugs, or, Why I Believe in Combinatorial Testing. Paul E. Black National Institute of Standards and Technology http://www.nist.gov/ paul.black@nist.gov. Outline. SAMATE, my current program, briefly Some tough and bizarre bugs How many conditions do faults need?

504 views • 36 slides

Jaclyn Bibby , Jens Thomas, Olga Mayans and Daniel Rigden Institute of Integrative Biology

449 views • 31 slides

Object detection

Object detection. Presented by Minh Hoai Nguyen Date: 28 March 2007. Object detection?. What we want. Miss a face!. Happy face!. Scanning window. Train a classifier on a fixed size window. Outline. Object Detection Using the Statistics of Parts

526 views • 25 slides

EN61000-4-6 Immunity to conducted disturbances, induced by radio-frequency fields ?????????????????

EN61000-4-6 Immunity to conducted disturbances, induced by radio-frequency fields ?????????????????. Provided By PH Yuan. ???????. ???? : 9KHz to 80MHz ???????????? , ????? , ???????? , ??? , ????????????????????? - ??????????????. ????. *** ??????????? (rms) ?????. ????????.

635 views • 25 slides

Automatic Clustering & Classification

Automatic Clustering & Classification. Team : Yang Priyanka Jithesh Arun. Agenda. Introduction to Clustering and Categorization. Types of Clustering Application of Clustering Application of Categorization Example (Quintara, NCSU Libraries)

551 views • 25 slides

Unsupervised Learning of Narrative Event Chains

Unsupervised Learning of Narrative Event Chains. Original paper by: Nate Chambers and Dan Jurafsky in ACL 2008 This presentation for discussion created by: Peter Clark (Jan 2009)

396 views • 22 slides

High Throughput Computing and Protein Structure

High Throughput Computing and Protein Structure. Stephen E. Hamby. Overview. Introduction To Protein Structure Dihedral Angles Previous Work Support Vector Regression Optimisation Prediction Results Conclusions. Introduction To Protein Structure.

364 views • 20 slides

On-Line Handwriting Recognition

On-Line Handwriting Recognition. Transducer device (digitizer) Input: sequence of point coordinates with pen-down/up signals from the digitizer Stroke: sequence of points from pen-down to pen-up signals Word: sequence of one or more strokes. System Overview. Pre-processing

555 views • 18 slides

Parallel Computing

437 views • 14 slides

CMP Synchronization

CMP Synchronization. Koushik Chakraborty Anu Vaidyanathan Philip Wells. Outline. Problem Overview Mutex Characterization Lock Arbiter Optimization Conclusions. Problem. Cost of Synchronization in a CMP (Focus on Mutex) Waiting on Contention Lock Transfer Mechanism

213 views • 11 slides

cs498dm Software Testing

Darko Marinov January 26, 2012. cs498dm Software Testing. Administrative Info. Mailing list confirmed last time Any questions about the course overview? Schedule (order set but dates are tentative) Syllabus Project: testing Java PathFinder Textbook recommended

229 views • 11 slides

Power Tool and Extension Cord Safety

Power Tool and Extension Cord Safety. Extension Cord Safety. 2. A cord not marked for outdoor use is to be used indoors only Inspect cord before each use. Do not use if damaged. Repair or replace cord. Damaged cords can cause short circuits, shocks, or fires.

343 views • 6 slides

Data Mining Classification: Basic Concepts,

Data Mining Classification: Basic Concepts,. Lecture Notes for Chapter 4 - 5 Introduction to Data Mining by Tan, Steinbach, Kumar. Classification: Definition. Given a collection of records ( training set ) Each record contains a set of attributes , one of the attributes is the class .

226 views • 0 slides