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347
K.B.: MultiInterval Discretization of ContinuousValued Attributes for Classication Learning. In:
 IJCAI.
, 1993
"... Abstract Since most realworld applications of classification learning involve continuousvalued attributes, properly addressing the discretization process is an important problem. This paper addresses the use of the entropy minimization heuristic for discretizing the range of a continuousvalued a ..."
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Cited by 832 (7 self)
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Abstract Since most realworld applications of classification learning involve continuousvalued attributes, properly addressing the discretization process is an important problem. This paper addresses the use of the entropy minimization heuristic for discretizing the range of a continuousvalued
Nonparametric estimation of average treatment effects under exogeneity: a review
 REVIEW OF ECONOMICS AND STATISTICS
, 2004
"... Recently there has been a surge in econometric work focusing on estimating average treatment effects under various sets of assumptions. One strand of this literature has developed methods for estimating average treatment effects for a binary treatment under assumptions variously described as exogen ..."
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Cited by 630 (25 self)
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as exogeneity, unconfoundedness, or selection on observables. The implication of these assumptions is that systematic (for example, average or distributional) differences in outcomes between treated and control units with the same values for the covariates are attributable to the treatment. Recent analysis has
Attribute Similarity and Event Sequence Similarity in Data Mining
, 1998
"... In data mining and knowledge discovery, similarity between objects is one of the central concepts. A measure of similarity can be userdefined, but an important problem is defining similarity on the basis of data. In this thesis we consider two kinds of similarity notions: similarity between binary ..."
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Cited by 6 (0 self)
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valued attributes and between event sequences. Traditional approaches for defining similarity between two attributes typically consider only the values of those two attributes, not the values of any other attributes in the relation. Such similarity measures are often useful, but unfortunately
Convex Adversarial Collective Classification
"... In this paper, we present a novel method for robustly performing collective classification in the presence of a malicious adversary that can modify up to a fixed number of binaryvalued attributes. Our method is formulated as a convex quadratic program that guarantees optimal weights against a worst ..."
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Cited by 6 (2 self)
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In this paper, we present a novel method for robustly performing collective classification in the presence of a malicious adversary that can modify up to a fixed number of binaryvalued attributes. Our method is formulated as a convex quadratic program that guarantees optimal weights against a
Limitations of Exemplar Models of MultiAttribute Probabilistic Inference
"... Observers were presented with pairs of objects varying along binaryvalued attributes and learned to predict which member of each pair had a greater value on a continuously varying criterion variable. The predictions from exemplar models of categorization were contrasted with classic alternative mod ..."
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Cited by 11 (0 self)
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Observers were presented with pairs of objects varying along binaryvalued attributes and learned to predict which member of each pair had a greater value on a continuously varying criterion variable. The predictions from exemplar models of categorization were contrasted with classic alternative
The MONK's Problems A Performance Comparison of Different Learning Algorithms
, 1991
"... This report summarizes a comparison of different learning techniques which was performed at the 2nd European Summer School on Machine Learning, held in Belgium during summer 1991. A variety of symbolic and nonsymbolic learning techniques  namely AQ17DCI, AQ17HCI, AQ17FCLS, AQ14NT, AQ15GA, Ass ..."
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Cited by 201 (15 self)
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is represented by six discretevalued attributes. Each problem involves learning a binary function defined over this domain, from a sample of training examples of this function. Experiments were performed with and without noise in the training examples. One significant characteristic of this comparison
Value Grouping for Binary Decision Trees
, 1995
"... The tests associated with the internal nodes of a binary decision tree can take on a variety of forms; for instance, they can test whether a given attribute has a given value, or more generally, whether it has a value in a given set. This report examines whether allowing the latter form of test (whi ..."
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The tests associated with the internal nodes of a binary decision tree can take on a variety of forms; for instance, they can test whether a given attribute has a given value, or more generally, whether it has a value in a given set. This report examines whether allowing the latter form of test
The String Representation of Standard Attribute Syntaxes
 RFC 1488, University of Michigan, ISODE Consortium, Performance Systems International, NeXor Ltd
, 1993
"... Status of this Memo This document specifies an Internet standards track protocol for the Internet community, and requests discussion and suggestions for improvements. Please refer to the current edition of the "Internet Official Protocol Standards " (STD 1) for the standardization state an ..."
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Cited by 55 (17 self)
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octet strings should be usable in their native encoded form for display purposes. In particular, encoding rules for attribute syntaxes defining nonbinary values should produce strings that can be displayed with little or no translation by clients implementing the lightweight directory protocols.
Efficient Attributes for Anonymous Credentials
, 2008
"... We extend the CamenischLysyanskaya anonymous credential system such that selective disclosure of attributes becomes highly efficient. The resulting system significantly improves upon existing approaches, which suffer from a linear complexity in the total number of attributes. This limitation makes ..."
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Cited by 21 (3 self)
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of all proofs of possession. The core idea is to encode discrete binary and finiteset attribute values as prime numbers. We use the divisibility property for efficient proofs of their presence or absence. We additionally contribute efficient methods for conjunctions and disjunctions. The system builds
BLOSOM: A Framework for Mining Arbitrary Boolean Expressions over Attribute Sets
 IN: PROCEEDINGS OF THE 12TH INTERNATIONAL CONFERENCE ON KNOWLEDGE DISCOVERY AND DATA MINING (KDD 2006
, 2006
"... We introduce a novel framework (BLOSOM) for mining (frequent) boolean expressions over binaryvalued datasets. We organize the space of boolean expressions into four categories: pure conjunctions, pure disjunctions, conjunction of disjunctions, and disjunction of conjunctions. For each category, ..."
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Cited by 12 (5 self)
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We introduce a novel framework (BLOSOM) for mining (frequent) boolean expressions over binaryvalued datasets. We organize the space of boolean expressions into four categories: pure conjunctions, pure disjunctions, conjunction of disjunctions, and disjunction of conjunctions. For each category
Results 1  10
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