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Classifier-Training published presentations and documents on DocSlides.

Supervised machine learning
Supervised machine learning
by karlyn-bohler
01/24/2012. Agenda. 0. Introduction of machine...
Biomarker and Classifier Selection in Diverse Genetic Datasets
Biomarker and Classifier Selection in Diverse Genetic Datasets
by pamella-moone
James . Lindsay. 1. Ed . Hemphill. 2. Chih. Lee....
Learning Thesauruses and Knowledge Bases
Learning Thesauruses and Knowledge Bases
by marina-yarberry
T. hesaurus induction and relation extraction. Wh...
SUPPORT VECTOR MACHINES ABHISHEK MADIRAJU
SUPPORT VECTOR MACHINES ABHISHEK MADIRAJU
by pasty-toler
INTRODUCTION. An approach for classification that...
Support Vector Machines (SVM)
Support Vector Machines (SVM)
by luanne-stotts
Chapter 09. Disclaimer: . This PPT is modified ba...
Feature Selection in Classification
Feature Selection in Classification
by debby-jeon
and R Packages. Houtao Deng. houtao_deng@intuit.c...
Non-linear classifiers Neural networks
Non-linear classifiers Neural networks
by liane-varnes
Linear classifiers on pixels are bad. Solution 1:...
Interpolants as Classifiers
Interpolants as Classifiers
by min-jolicoeur
Rahul Sharma. Joint work with . Aditya. . Nori. ...
Numeral Classifiers and the White Horse Paradox
Numeral Classifiers and the White Horse Paradox
by tawny-fly
李秉昱. . Byeong-uk Yi. University of Toronto...
Sharing Features Between Objects and Their Attributes
Sharing Features Between Objects and Their Attributes
by lois-ondreau
Sung . Ju. Hwang. 1. , . Fei. Sha. 2. and Kris...
Finite Mixture Models and EM Algorithm
Finite Mixture Models and EM Algorithm
by liane-varnes
McLachlan, G., & Peel, D. (2001). . Finite m...
Bram Cappers b.c.m.cappers@tue.nl
Bram Cappers b.c.m.cappers@tue.nl
by briana-ranney
Jarke. van Wijk. j.j.v.wijk@tue.nl. 2. /12. A. d...
Performance Evaluation for Learning Algorithms
Performance Evaluation for Learning Algorithms
by celsa-spraggs
. Nathalie Japkowicz. School of Electrical E...
ADSP - Oral presentation
ADSP - Oral presentation
by phoebe-click
3D Accelerometer. Presenter : . Chen Yu. R0094049...
Sense-level Subjectivity Analysis
Sense-level Subjectivity Analysis
by karlyn-bohler
1. What is Subjectivity?. Private state:. state ...
ECG Signal processing (2)
ECG Signal processing (2)
by olivia-moreira
ECE, UA. ECG signal processing - Case [1]. Diagno...
POLYMORPHISM AND VARIANT ANALYSIS
POLYMORPHISM AND VARIANT ANALYSIS
by conchita-marotz
Matt . Hudson . Crop Sciences. NCSA. . HPCB...
Zhuode
Zhuode
by liane-varnes
Liu. University of Texas at Austin. CS 381V: Vis...
Machine Learning Applied in Product Classification
Machine Learning Applied in Product Classification
by luanne-stotts
Jianfu Chen. Computer Science Department. Stony B...
Performance Evaluation for Learning Algorithms
Performance Evaluation for Learning Algorithms
by celsa-spraggs
. Nathalie Japkowicz. School of Electrical E...
Active Sampling for Entity Matching
Active Sampling for Entity Matching
by tatiana-dople
Aditya. . Parameswaran. Stanford University. Joi...
Model Evaluation
Model Evaluation
by min-jolicoeur
Metrics for Performance Evaluation. How to evalua...
Joint Object-Material Category
Joint Object-Material Category
by tatiana-dople
Segmentation from Audio-Visual . Cues. Anurag Arn...
SUPER: Towards Real-time Event Recognition in Internet Vide
SUPER: Towards Real-time Event Recognition in Internet Vide
by alexa-scheidler
Yu-Gang . Jiang. School of Computer Science. Fuda...
It doesn't matter what you do, but it does matter who does
It doesn't matter what you do, but it does matter who does
by pasty-toler
Martin Shepperd, Brunel U. Tracy Hall, Brunel U. ...
An Introduction of
An Introduction of
by alida-meadow
. Support Vector Machine. Courtesy of . Jinwei. ...
An Efficient GPGPU Implementation of
An Efficient GPGPU Implementation of
by danika-pritchard
Viola-Jones Classifier . based Face Detection Alg...
Unsupervised Learning of Visual Sense Models for Polysemous
Unsupervised Learning of Visual Sense Models for Polysemous
by tatyana-admore
Kate Saenko Trevor Darrell. Deepak. Polysemy. Amb...
A Robust and Energy-Efficient Classifier
A Robust and Energy-Efficient Classifier
by olivia-moreira
Using Brain-Inspired . Hyperdimensional Computing...
Twitter as a Corpus for Sentiment Analysis and Opinion Mini
Twitter as a Corpus for Sentiment Analysis and Opinion Mini
by tatiana-dople
Adam. Rosenberg, Leandra Irvine, Gus . Logsdon. ...
Spam Email Detection
Spam Email Detection
by pasty-toler
Ethan Grefe. December . 13, . 2013. Motivation. S...
Efficient Logistic Regression with Stochastic Gradient Desc
Efficient Logistic Regression with Stochastic Gradient Desc
by tatiana-dople
William Cohen. 1. SGD for Logistic Regression. 2....
Interpolants
Interpolants
by aaron
as Classifiers. Rahul Sharma. Joint work with . ...
An Introduction to Machine Learning
An Introduction to Machine Learning
by pasty-toler
Presented to LING-7800 . Shumin . Wu. Prepared by...
Sarcasm Detection on
Sarcasm Detection on
by liane-varnes
Twitter . A Behavioral Modeling . Approach. Ashwi...
Minimum Redundancy and Maximum Relevance Feature Selection
Minimum Redundancy and Maximum Relevance Feature Selection
by kittie-lecroy
Hang Xiao. Background. Feature. a . feature. is ...
Rotten or Fresh?
Rotten or Fresh?
by liane-varnes
NLP applied to Sentiment Analysis. Two NLP tasks....
Evaluating optimization algorithms: bounds on the performa
Evaluating optimization algorithms: bounds on the performa
by ellena-manuel
unseen problems. David . Corne. , Alan Reynolds....
Integration II
Integration II
by phoebe-click
Prediction. Kernel-based data integration. SVMs a...
2012 ijarcsse all
2012 ijarcsse all
by lois-ondreau
Rights Reserved Page | 85 Volume 2...