'Roc curve' presentation slideshows

Information Retrieval

Information Retrieval. CSE 8337 (Part IV) Spring 2011 Some Material for these slides obtained from: Modern Information Retrieval by Ricardo Baeza -Yates and Berthier Ribeiro-Neto http://www.sims.berkeley.edu/~hearst/irbook/

1.62k views • 142 slides

Stage-Specific Survivability Prediction Models across Different Cancer Types

Stage-Specific Survivability Prediction Models across Different Cancer Types. Elham Sagheb Hossein Pour 1 and Rohit J. Kate 2 1 Marshfield Clinic Research Institute 2 University of Wisconsin-Milwaukee.

538 views • 42 slides

?????? Signal Detection Theory (SDT)

?????? Signal Detection Theory (SDT). ??? ?????????. ??. ????????????????? ?????????? ????????? ????? SDT ???????????. ??????????????? ?????????????? ? ????????. ???????????????????????. ???? ???????? ????????? ???????? ???????? ????????? ????????? ???????? ???????? ????? ????????.

1.77k views • 39 slides

Institute of Liver & Biliary Sciences

APASL Cairo 2014. Institute of Liver & Biliary Sciences. Can WHVP be recommended as a routine surrogate marker of fibrosis !. Dr S K Sarin Institute of Liver and Biliary Sciences (ILBS), New Delhi shivsarin@gmail.com. D-1, Vasant Kunj, Delhi, India www.ilbs.in. Outline.

623 views • 36 slides

Final Presentation Group 2 Porto, 2 nd May 2007 Medical Faculty of Oporto

the reporting of Diagnostic accuracy studies in gastroenterology and hepatology literature . A STARD assessment. Final Presentation Group 2 Porto, 2 nd May 2007 Medical Faculty of Oporto. Topics. Introduction Methods Results Discussion and Conclusions Acknowledgements. Introduction.

452 views • 35 slides

Decision making as a model

Decision making as a model. 2. Statistics and decision making. Bayesian statistics: p(H|D) ? p(H) ?p(D|H) If H refers to possible values of ? : pdf( ? |D) ? pdf( ? ) ?L ( ? |D) NB: L: Likelihood function!.

395 views • 29 slides

Outline

383 views • 27 slides

Supervised gene expression data analysis using SVMs and MLPs

Supervised gene expression data analysis using SVMs and MLPs. e-mail: valenti@disi.unige.it. Giorgio Valentini. Outline. A real problem: Lymphoma gene expression data analysis by machine learning methods: Diagnosis of tumors using a supervised approach

415 views • 25 slides

A Critical View of context

442 views • 22 slides

...visualizing classifier performance in R

...visualizing classifier performance in R. Tobias Sing, Ph.D. (joint work with Oliver Sander) Modeling & Simulation Novartis Pharma AG 3 rd BaselR meeting (Oct 13, 2010). Q: When can ROCR be useful for you? Not only in machine learning!.

329 views • 21 slides

A Comparative Evaluation of Three Skin Color Detection Approaches

362 views • 20 slides

FEDERAL UNIVERSITY OF UBERLANDIA

288 views • 17 slides

Discussant: Chen Zhou De Nederlandsche Bank

270 views • 15 slides

Active Learning for Unbalanced Data in the Challenge with Multiple Models and Biasing

Active Learning for Unbalanced Data in the Challenge with Multiple Models and Biasing. Yukun Chen Subramani Mani Discovery Systems Lab (DSL) Department of Biomedical Informatics Vanderbilt University May 2010. Outline. Introduction Datasets in the challenge Probabilistic models

232 views • 14 slides

How to Control Acceptance Threshold for Biometric Signatures with Different Confidence Values?

How to Control Acceptance Threshold for Biometric Signatures with Different Confidence Values?. Yasushi Makihara ( ?? ? ) , Md. Altab Hossain , Yasushi Yagi ( ?? ?? ) ??? ? ICPR 2010. Introduction. Biometrics-based verification Quality measure False Acceptance Rate(FAR)

312 views • 14 slides

Performance measures

Performance measures. Morten Nielsen. Performance measures. Meas Pred 0.4050 0.8344 0.9373 1.0000 0.8161 0.6388 0.6752 0.9841 0.0253 0.0000 0.3196 0.5388 0.6764 0.6247 0.1872 0.1921 0.4220 0.6546 0.6545 0.6546 0.7917 0.1342 0.4405 0.3551 0.1548 0.0000 0.2740 0.1993

250 views • 14 slides

INFOMR Project

181 views • 11 slides

CAP and ROC curves

CAP and ROC curves. Cumulative Accuracy Profiles (CAP) . We first rank companies by their default probabilities (i.e., credit scores) as predicted by the model, from highest to lowest.

775 views • 10 slides

ROC Curve Demo

ROC Curve Demo .

218 views • 9 slides

227 views • 9 slides