Rule Induction
Pruning methods for rule induction
... for rule-induction methods can help in reducing the complexity of rule sets by reducing the number of generated rules, without adversely affecting the predictive ...from rule-induction ...
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Hierarchical Maximum Pattern Matching with Rule Induction Approach for Sentence Parsing
... Table 2 shows the details parser ratio of each syntactic structure. For the result, it has highest ratio about 80% on sentence level parser. In test data, the token of each string are more than 6, it has more probability ...
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Knowledge Generation with Rule Induction in Cancer Omics
... Technical feature selection strategies aim to reduce data dimensionality by removing redundant and/or irrelevant features or by transforming the original high-dimensional feature space to an analytically equivalent but ...
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Chinese Word Spelling Correction Based on Rule Induction
... In the previous section, the rule induction is built in training phase. We will describe the test phase of the framework in this section. The word segmentation and part of speech (POS) labeling are the same ...
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Correlation Associative Rule Induction Algorithm Using ACO
... association rule mining and classification to build more accu- rate classifier model than traditional classification algorithm like decision tree and rule induction ...associative rule set. ...
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Towards Efficient Named Entity Rule Induction for Customizability
... to rule induction for IE focus on rule-based systems based on the cascading gram- mar formalism exemplified by the Common Pat- tern Specification Language (CPSL) (Appelt and Onyshkevych, 1998), where ...
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A Rule Induction Approach to Modeling Regional Pronunciation Variation
... Coling dvi A Rule Induction Approach to Modeling Regional Pronunciation Variation V?eronique Hoste and Steven Gillis and Walter Daelemans? CNTS Language Technology Group University of Antwerp Universi[.] ...
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Hybrid Fuzzy-Rough Rule Induction and Feature Selection
... The classifiers themselves are obtained from the WEKA toolkit [28] and ROSE software [23], and are evaluated using their default parameter settings. Additionally, two approaches for nearest neighbor classification are ...
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Performance Analysis of Hybrid Swarm Intelligence Rule Induction Algorithm
... base. Rule induction is used to extract information from data base and display it in IF-THEN rule ...hybrid rule induction algorithm using Cooperative Particle Swarm (PSO) with Tabu ...
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Exception Included, Ordered Rule Induction from the Set of Exemplars (ExIORISE)
... older rule / decision- tree based algorithms perform pretty well with small data ...the rule set and ordering of the rules using weights beforehand are integrated with the classical RISE algorithm to ...
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A novel rule induction algorithm with improved handling of continuous valued attributes
... novel rule induction algorithm, a simple and efficient method which is able to deal with either discrete or continuous variables without the need to preprocess ...
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A Comparison of the Quality of Rule Induction from Inconsistent Data Sets and Incomplete Data Sets
... We implemented the conventional MLEM2 algorithm and the local probabilistic version of MLEM2 algorithm for rule induction. We also developed a program to classify cases with induced rule sets and ...
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Data- and expert-driven rule induction and filtering framework for functional interpretation and description of gene sets
... the rule induction process should be automated or expert- ...automated rule induc- ...of rule induc- tion should be ...the rule induction algorithm part, the user can define sta- ...
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Detecting Problematic Turns in Human Machine Interactions: Rule induction Versus Memory based Learning Approaches
... both rule- induction and memory-based learning techniques to data obtained with a Dutch train time-table information system, the current paper demonstrates that the aforementioned features indeed lead to a ...
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Preceding rule induction with instance reduction methods
... In this paper, we have mentioned different instance reduction techniques, and applied them as preprocessing before CN2 algorithm. Our experiments showed that for most datasets, pruning the training set using AllKnn, ENN ...
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An Investigation of Rule Induction Based Prediction Systems
... Many software development environments consist of a complex set of interrelationships. Using the entire dataset without attempting to understand these factors can lead to substantially sub-optimal results. Preliminary ...
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Morphological Rule Induction for Terminology Acquisition
... daille col00 1 dvi Morphological Rule Induction for Terminology Acquisition B?eatrice Daille IRIN, 2, rue de la Houssini?ere, BP 92208, 44322 Nantes Cedex 3 France daille@irin univ nantes fr Abstract[.] ...
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Rule induction for global explanation of trained models
... Most of the above-mentioned techniques output a ranked list of the most significant features for a model. Several approaches, especially when the input is an image, visualize these features as im- age segments (Erhan et ...
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Bayesian learning and the psychology of rule induction
... Frank and Tenenbaum (2011) attempt to account for various experimental results in the domain of rule- learning. According to Frank and Tenenbaum (2011), their models are psychologically implausible, but consti- ...
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Learning Bias and Phonological Rule Induction
... We show that OSTIA, a general-purpose transducer induction algorithm, was incapable of learning simple phonological rules like flapping.. These biases are so fundamental to generative ph[r] ...
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