Results 1 - 10 of 46,066

Thumbs up? Sentiment Classification using Machine Learning Techniques

by Bo Pang, Lillian Lee, Shivakumar Vaithyanathan - IN PROCEEDINGS OF EMNLP , 2002
"... We consider the problem of classifying documents not by topic, but by overall sentiment, e.g., determining whether a review is positive or negative. Using movie reviews as data, we find that standard machine learning techniques definitively outperform human-produced baselines. However, the three mac ..."
Abstract - Cited by 1101 (7 self) - Add to MetaCart
We consider the problem of classifying documents not by topic, but by overall sentiment, e.g., determining whether a review is positive or negative. Using movie reviews as data, we find that standard machine learning techniques definitively outperform human-produced baselines. However, the three

The use of the area under the ROC curve in the evaluation of machine learning algorithms

by Andrew P. Bradley - PATTERN RECOGNITION , 1997
"... In this paper we investigate the use of the area under the receiver operating characteristic (ROC) curve (AUC) as a performance measure for machine learning algorithms. As a case study we evaluate six machine learning algorithms (C4.5, Multiscale Classifier, Perceptron, Multi-layer Perceptron, k-Ne ..."
Abstract - Cited by 685 (3 self) - Add to MetaCart
In this paper we investigate the use of the area under the receiver operating characteristic (ROC) curve (AUC) as a performance measure for machine learning algorithms. As a case study we evaluate six machine learning algorithms (C4.5, Multiscale Classifier, Perceptron, Multi-layer Perceptron, k

Support Vector Machine Active Learning with Applications to Text Classification

by Simon Tong , Daphne Koller - JOURNAL OF MACHINE LEARNING RESEARCH , 2001
"... Support vector machines have met with significant success in numerous real-world learning tasks. However, like most machine learning algorithms, they are generally applied using a randomly selected training set classified in advance. In many settings, we also have the option of using pool-based acti ..."
Abstract - Cited by 735 (5 self) - Add to MetaCart
Support vector machines have met with significant success in numerous real-world learning tasks. However, like most machine learning algorithms, they are generally applied using a randomly selected training set classified in advance. In many settings, we also have the option of using pool

Probabilistic Outputs for Support Vector Machines and Comparisons to Regularized Likelihood Methods

by John C. Platt - ADVANCES IN LARGE MARGIN CLASSIFIERS , 1999
"... The output of a classifier should be a calibrated posterior probability to enable post-processing. Standard SVMs do not provide such probabilities. One method to create probabilities is to directly train a kernel classifier with a logit link function and a regularized maximum likelihood score. Howev ..."
Abstract - Cited by 1051 (0 self) - Add to MetaCart
The output of a classifier should be a calibrated posterior probability to enable post-processing. Standard SVMs do not provide such probabilities. One method to create probabilities is to directly train a kernel classifier with a logit link function and a regularized maximum likelihood score

Ptolemy: A Framework for Simulating and Prototyping Heterogeneous Systems

by Joseph Buck, Soonhoi Ha, Edward A. Lee, David G. Messerschmitt , 1992
"... Ptolemy is an environment for simulation and prototyping of heterogeneous systems. It uses modern object-oriented software technology (C++) to model each subsystem in a natural and efficient manner, and to integrate these subsystems into a whole. Ptolemy encompasses practically all aspects of design ..."
Abstract - Cited by 571 (89 self) - Add to MetaCart
Ptolemy is an environment for simulation and prototyping of heterogeneous systems. It uses modern object-oriented software technology (C++) to model each subsystem in a natural and efficient manner, and to integrate these subsystems into a whole. Ptolemy encompasses practically all aspects

The Alignment Template Approach to Statistical Machine Translation

by Franz Josef Och, Hermann Ney , 2004
"... A phrase-based statistical machine translation approach — the alignment template approach — is described. This translation approach allows for general many-to-many relations between words. Thereby, the context of words is taken into account in the translation model, and local changes in word order f ..."
Abstract - Cited by 480 (26 self) - Add to MetaCart
–English Canadian Hansards task, the alignment template system obtains significantly better results than a single-word-based translation model. In the Chinese–English 2002 National Institute of Standards and Technology (NIST) machine translation evaluation it yields statistically significantly better NIST scores

Sesame: A Generic Architecture for Storing and Querying RDF and RDF Schema

by Jeen Broekstra, Arjohn Kampman, Frank Van Harmelen , 2002
"... RDF and RDF Schema are two W3C standards aimed at enriching the Web with machine-processable semantic data. ..."
Abstract - Cited by 543 (11 self) - Add to MetaCart
RDF and RDF Schema are two W3C standards aimed at enriching the Web with machine-processable semantic data.

Benchmarking Least Squares Support Vector Machine Classifiers

by Tony Van Gestel, Johan A. K. Suykens, Bart Baesens, Stijn Viaene, Jan Vanthienen, Guido Dedene, Bart De Moor, Joos Vandewalle - NEURAL PROCESSING LETTERS , 2001
"... In Support Vector Machines (SVMs), the solution of the classification problem is characterized by a (convex) quadratic programming (QP) problem. In a modified version of SVMs, called Least Squares SVM classifiers (LS-SVMs), a least squares cost function is proposed so as to obtain a linear set of eq ..."
Abstract - Cited by 476 (46 self) - Add to MetaCart
In Support Vector Machines (SVMs), the solution of the classification problem is characterized by a (convex) quadratic programming (QP) problem. In a modified version of SVMs, called Least Squares SVM classifiers (LS-SVMs), a least squares cost function is proposed so as to obtain a linear set

Fast and accurate short read alignment with Burrows-Wheeler transform

by Heng Li, Richard Durbin - BIOINFORMATICS, 2009, ADVANCE ACCESS , 2009
"... Motivation: The enormous amount of short reads generated by the new DNA sequencing technologies call for the development of fast and accurate read alignment programs. A first generation of hashtable based methods has been developed, including MAQ, which is accurate, feature rich and fast enough to a ..."
Abstract - Cited by 2096 (24 self) - Add to MetaCart
reads, e.g. from Illumina sequencing machines, and color space reads from AB SOLiD machines. Evaluations on both simulated and real data suggest that BWA is ∼10–20X faster than MAQ while achieving similar accuracy. In addition, BWA outputs alignment in the new standard SAM format. Variant calling

A tutorial on support vector regression

by Alex J. Smola, Bernhard Schölkopf , 2004
"... In this tutorial we give an overview of the basic ideas underlying Support Vector (SV) machines for function estimation. Furthermore, we include a summary of currently used algorithms for training SV machines, covering both the quadratic (or convex) programming part and advanced methods for dealing ..."
Abstract - Cited by 865 (3 self) - Add to MetaCart
In this tutorial we give an overview of the basic ideas underlying Support Vector (SV) machines for function estimation. Furthermore, we include a summary of currently used algorithms for training SV machines, covering both the quadratic (or convex) programming part and advanced methods for dealing
Results 1 - 10 of 46,066