'Original training data' presentation slideshows

Text Categorization

Text Categorization. CSE 454. Course Overview. Info Extraction. Ecommerce. P2P. Web Services Semantic Web. Security. Datamining. Case Studies: Nutch, Google , Altavista. Information Retrieval Precision vs Recall Inverted Indicies. Crawler Architecture. Synchronization & Monitors.

638 views • 63 slides

The MSR ESL Assistant: Detecting and correcting non-native errors in English

The MSR ESL Assistant: Detecting and correcting non-native errors in English. Michael Gamon, Chris Brockett, William B. Dolan, Jianfeng Gao, Dmitriy Belenko (Microsoft Research), Alexandre Klementiev (University of Illinois at Urbana Champaign), Claudia Leacock (Butler Hill Group).

469 views • 38 slides

Bagging

527 views • 32 slides

Ensemble Classifiers

Ensemble Classifiers. Prof. Navneet Goyal. Ensemble Classifiers. Introduction & Motivation Construction of Ensemble Classifiers Boosting (Ada Boost) Bagging Random Forests Empirical Comparison. Introduction & Motivation. Suppose that you are a patient with a set of symptoms

595 views • 32 slides

Deep Learning

Deep Learning. Roger S. Gaborski. Visual System Visual cortex is defined in terms of hierarchical regions: V1 ? V2 ? V3 ? V4 ? V5 ? MST Some regions may be bypassed, depending on the features being extracted

409 views • 28 slides

Bayesian Learning

Bayesian Learning. Rong Jin. Outline. MAP learning vs. ML learning Minimum description length principle Bayes optimal classifier Bagging. Maximum Likelihood Learning (ML). Find the model that best model by maximizing the log-likelihood of the training data Logistic regression

608 views • 27 slides

Hierarchical distributed data classification in wireless sensor networks

Hierarchical distributed data classification in wireless sensor networks. Xu Cheng, Ji Xu , Jian Pei, Jiangchuan Liu School of Computing Science, Simon Fraser University Burnaby, British Columbia, Canada (To appear in Computer Communication 2010, Elsevier). Presented by Binh Tran

390 views • 26 slides

CS 388: Natural Language Processing: N-Gram Language Models

752 views • 22 slides

CS 388: Natural Language Processing: N-Gram Language Models

575 views • 22 slides

Detection by Detections: Non-parametric Detector Adaptation for a Video

Detection by Detections: Non-parametric Detector Adaptation for a Video. Outline. Introduction Non-parametric detector adaption Binary codes with a vocabulary tree Similarity measure of the binary codes Transfer classification Identity grouping of detections Experiment Conclusion.

354 views • 22 slides

CSCI 5622 Machine Learning Ensembles; Bagging and Boosting

CSCI 5622 Machine Learning Ensembles; Bagging and Boosting. DATE READ DUE Today, Oct 12 Bagging & Boosting Exper. 1 plan Wed, Oct 14 Stacking & Rand Forests Literature Review Mon, Oct 19 Clustering Peer Fdbk Lit Rev www.RodneyNielsen.com/teaching/CSCI5622-F09/ Instructor: Rodney Nielsen

416 views • 20 slides