Quarter 2
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LIBSVM -- A Library for Support Vector Machines
Version 3.11 released on November 5, 2011. We have a new make.m to easily install matlab/octave interface on windows/unix/mac. We now have a nice page LIBSVM data sets providing problems in LIBSVM format. A practical guide to SVM classification is available now!
AIxploratorium - Decision Trees
Wanna hear the story : You are in the office pool, currently betting on the outcome of the basketball game next week, between the MallRats and the Chinooks . You have to decide which team will win, then bet on that team. Of course, you could just guess, or flip a coin. Here we present a way that (typically) will do better: by using observations about the past performance of the teams. Topics
Conditional random fields (CRFs) are a class of statistical modelling method often applied in pattern recognition and machine learning , where they are used for structured prediction . Whereas an ordinary classifier predicts a label for a single sample without regard to "neighboring" samples, a CRF can take context into account; e.g., the linear chain CRF popular in natural language processing predicts sequences of labels for sequences of input samples. CRFs are a type of discriminative undirected probabilistic graphical model . It is used to encode known relationships between observations and construct consistent interpretations. It is often used for labeling or parsing of sequential data, such as natural language text or biological sequences [ 1 ] and in computer vision . [ 2 ] Specifically, CRFs find applications in shallow parsing , [ 3 ] named entity recognition [ 4 ] and gene finding , among other tasks, being an alternative to the related hidden Markov models .
Conditional random field - Wikipedia, the free encyclopedia
Generally speaking, the chi-square test is a statistical test used to examine differences with categorical variables. There are a number of features of the social world we characterize through categorical variables - religion, political preference, etc. To examine hypotheses using such variables, use the chi-square test. One of the more interesting goodness-of-fit applications of the chi-square test is to examine issues of fairness and cheating in games of chance, such as cards, dice, and roulette. Since such games usually involve wagering, there is significant incentive for people to try to rig the games and allegations of missing cards, "loaded" dice, and "sticky" roulette wheels are all too common.
QMSS e-Lessons | About the Chi-Square Test
The curse of dimensionality refers to various phenomena that arise when analyzing and organizing high-dimensional spaces (often with hundreds or thousands of dimensions) that do not occur in low-dimensional settings such as the physical space commonly modeled with just three dimensions. There are multiple phenomena referred to by this name in domains such as sampling , combinatorics , machine learning and data mining . The common theme of these problems is that when the dimensionality increases, the volume of the space increases so fast that the available data becomes sparse. This sparsity is problematic for any method that requires statistical significance. In order to obtain a statistically sound and reliable result, the amount of data you need to support the result often grows exponentially with the dimensionality.
Curse of dimensionality - Wikipedia, the free encyclopedia
Latent semantic analysis - Wikipedia, the free encyclopedia
Latent semantic analysis ( LSA ) is a technique in natural language processing , in particular in vectorial semantics , of analyzing relationships between a set of documents and the terms they contain by producing a set of concepts related to the documents and terms. LSA assumes that words that are close in meaning will occur close together in text. A matrix containing word counts per paragraph (rows represent unique words and columns represent each paragraph) is constructed from a large piece of text and a mathematical technique called singular value decomposition (SVD) is used to reduce the number of columns while preserving the similarity structure among rows.
In linear algebra , the singular value decomposition ( SVD ) is a factorization of a real or complex matrix , with many useful applications in signal processing and statistics . where U is an m×m real or complex unitary matrix , Σ is an m×n rectangular diagonal matrix with nonnegative real numbers on the diagonal, and V* (the conjugate transpose of V ) is an n×n real or complex unitary matrix. The diagonal entries Σ i , i of Σ are known as the singular values of M . The m columns of U and the n columns of V are called the left singular vectors and right singular vectors of M , respectively.
Singular value decomposition - Wikipedia, the free encyclopedia
LING 571
Aims : To master algorithms for associating deep or elaborated linguistic structures with naturally occurring linguistic data. We will stress two cross-cutting themes in the course: evaluation metrics and dealing with ambiguity. To a lesser degree we will also investigate multilingual resources.
Prover9 Download
Prover9, Mace4, and several related programs come packaged in a system called LADR (Library for Automated Deduction Research). If you install one of these LADR packages, you will get command-line programs. (The programs are run by typing commands to a command prompt, terminal, or shell.)
Welcome to FrameNet | fndrupal
Welcome! This is the official website for the FrameNet Project, housed at the International Computer Science Institute in Berkeley, California. If you have questions or comments about either FrameNet or the website itself, Please post them in the forums. (Note that you will have to register before you can post to the forums.)
About WordNet - WordNet - About WordNet
WordNet® is a large lexical database of English. Nouns, verbs, adjectives and adverbs are grouped into sets of cognitive synonyms (synsets), each expressing a distinct concept. Synsets are interlinked by means of conceptual-semantic and lexical relations.Le WOLF (Wordnet Libre du Français) est une ressource lexicale sémantique (wordnet) libre pour le français. Le WOLF a été construit à partir du Princeton WordNet (PWN) et de diverses ressources multilingues (Sagot et Fišer 2008a, Sagot et Fišer 2008b, Fišer et Sagot 2008). Les lexèmes polysémiques ont été traités au moyen d'une approche reposant sur l'alignement en mots d'un corpus parallèle en cinq langues. Le lexique multilingue extrait a été désambiguïsé sémantiquement à l'aide des wordnets des langues concernées.
Benoît Sagot - WOLF
Longman English Dictionary Online
Search any word using the power of the Longman Dictionary of Contemporary English. The quickest and easiest way to look up any word while you are working on the web. Fully searchable contents of the A-Z text of the Longman Dictionary of Contemporary EnglishThe goal is to implement the CKY algorithm for a non-probabilistic context free grammar and to test the parser on a set of input sentences. A Chomsky Normal Form grammar is provided. To prepare for this assignment, read chapter 13 of Jurafsky and Martin (2nd Edition) and be sure you understand the CKY algorithm in Section 13.4. Note in particular why a CNF grammar is needed for the CKY algorithm. Create a CKYParser class that will take a context-free grammar in CNF and return all possible parses for a give sentence file.
Homework 2 — Ling571, Winter Qtr. 2010
Parser care package
Python start up package for parser writing . Includes toy grammar. Code for creating a grammar representation convenient for the parse.Ingush