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Bridging Causal Relevance and Pattern Discriminability: Mining Emerging Patterns from High-Dimensional Data

https://doi.org/10.1109/tkde.2012.218

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/3-540-44491-2_8openalex-snapshot

Information-Based Classification by Aggregating Emerging Patterns

inferredcites →https://doi.org/10.1007/3-540-45372-5_19openalex-snapshot

Instance-Based Classification by Emerging Patterns

inferredcites →https://doi.org/10.1007/3-540-45571-x_29openalex-snapshot

Making Use of the Most Expressive Jumping Emerging Patterns for Classification

inferredcites →https://doi.org/10.1007/3-540-46846-3_4openalex-snapshot

CAEP: Classification by Aggregating Emerging Patterns

inferredcites →https://doi.org/10.1007/978-1-4612-2748-9openalex-snapshot

Causation, Prediction, and Search

inferredcites →https://doi.org/10.1007/s10115-009-0267-2openalex-snapshot

Methods for mining frequent items in data streams: an overview

inferredcites →https://doi.org/10.1007/s10115-010-0309-9openalex-snapshot

RP-Miner: a relaxed prune algorithm for frequent similar pattern mining

inferredcites →https://doi.org/10.1007/s10115-010-0324-xopenalex-snapshot

Fuzzy emerging patterns for classifying hard domains

inferredcites →https://doi.org/10.1007/s10115-010-0335-7openalex-snapshot

Rule induction for uncertain data

inferredcites →https://doi.org/10.1007/s10115-010-0364-2openalex-snapshot

An integration of fuzzy association rules and WordNet for document clustering

inferredcites →https://doi.org/10.1007/s10994-006-6889-7openalex-snapshot

The max-min hill-climbing Bayesian network structure learning algorithm

inferredcites →https://doi.org/10.1016/c2009-0-27609-4openalex-snapshot

Probabilistic Reasoning in Intelligent Systems

inferredcites →https://doi.org/10.1016/j.ijar.2006.06.008openalex-snapshot

Towards scalable and data efficient learning of Markov boundaries

inferredcites →https://doi.org/10.1093/bioinformatics/18.5.725openalex-snapshot

Identifying good diagnostic gene groups from gene expression profiles using the concept of emerging patterns

inferredcites →https://doi.org/10.1093/bioinformatics/19.1.71openalex-snapshot

Simple rules underlying gene expression profiles of more than six subtypes of acute lymphoblastic leukemia (ALL) patients

inferredcites →https://doi.org/10.1093/bioinformatics/btg361openalex-snapshot

A CART-based approach to discover emerging patterns in microarray data

inferredcites →https://doi.org/10.1109/icdm.2001.989541openalex-snapshot

CMAR: accurate and efficient classification based on multiple class-association rules

inferredcites →https://doi.org/10.1109/tkde.2006.95openalex-snapshot

Fast discovery and the generalization of strong jumping emerging patterns for building compact and accurate classifiers

inferredcites →https://doi.org/10.1109/tkde.2007.190677openalex-snapshot

A Lazy Approach to Associative Classification

inferredcites →https://doi.org/10.1109/tkde.2010.153openalex-snapshot

Mining Discriminative Patterns for Classifying Trajectories on Road Networks

inferredcites →https://doi.org/10.1109/tkde.2010.241openalex-snapshot

Mining Low-Support Discriminative Patterns from Dense and High-Dimensional Data

inferredcites →https://doi.org/10.1137/1.9781611972733.40openalex-snapshot

CPAR: Classification based on Predictive Association Rules

inferredcites →https://doi.org/10.1137/1.9781611972757.19openalex-snapshot

HARMONY: Efficiently Mining the Best Rules for Classification

inferredcites →https://doi.org/10.1145/1150402.1150438openalex-snapshot

Fast mining of high dimensional expressive contrast patterns using zero-suppressed binary decision diagrams

inferredcites →https://doi.org/10.1145/1557019.1557083openalex-snapshot

Classification of software behaviors for failure detection

inferredcites →https://doi.org/10.1145/1656274.1656278openalex-snapshot

The WEKA data mining software

inferredcites →https://doi.org/10.1145/312129.312191openalex-snapshot

Efficient mining of emerging patterns

inferredcites →https://doi.org/10.1145/347090.347158openalex-snapshot

Exploring constraints to efficiently mine emerging patterns from large high-dimensional datasets

inferredcites →https://doi.org/10.1201/9781584888796.ch4openalex-snapshot

Causal Feature Selection

inferredcites →https://doi.org/10.1587/transinf.e95.d.1531openalex-snapshot

Classification Based on Predictive Association Rules of Incomplete Data

inferredcites →https://doi.org/10.5555/1577069.1577083openalex-snapshot

Supervised Descriptive Rule Discovery: A Unifying Survey of Contrast Set, Emerging Pattern and Subgroup Mining

inferredcites →https://doi.org/10.5555/1756006.1756013openalex-snapshot

Local Causal and Markov Blanket Induction for Causal Discovery and Feature Selection for Classification Part I: Algorithms and Empirical Evaluation

inferredcites →https://doi.org/10.5555/1953048.2021027openalex-snapshot

Efficient Structure Learning of Bayesian Networks using Constraints

inferredcites →https://doi.org/10.7551/mitpress/1754.001.0001openalex-snapshot

Causation, Prediction, and Search

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Detecting of PIU Behaviors Based on Discovered Generators and Emerging Patterns from Computer-Mediated Interaction Events

inferred← citeshttps://doi.org/10.1007/s10115-021-01550-yopenalex-snapshot

Mining discriminative itemsets in data streams using the tilted-time window model

inferred← citeshttps://doi.org/10.1007/s42979-023-01819-9openalex-snapshot

DAC: Discriminative Associative Classification

inferred← citeshttps://doi.org/10.1016/j.knosys.2023.110694openalex-snapshot

On causal structural learning algorithms: Oracles’ simulations and considerations

inferred← citeshttps://doi.org/10.1016/j.neucom.2016.09.119openalex-snapshot

Enhancing ELM by Markov Boundary based feature selection

inferred← citeshttps://doi.org/10.1109/cec.2015.7257257openalex-snapshot

A GA-based approach for mining membership functions and concept-drift patterns

inferred← citeshttps://doi.org/10.1109/icdm.2013.154openalex-snapshot

Markov Blanket Feature Selection with Non-faithful Data Distributions

inferred← citeshttps://doi.org/10.1109/tkde.2016.2578315openalex-snapshot

A Partial Correlation Statistic Structure Learning Algorithm Under Linear Structural Equation Models

inferred← citeshttps://doi.org/10.1109/tkde.2023.3266453openalex-snapshot

Directed Acyclic Graph Learning on Attributed Heterogeneous Network

inferred← citeshttps://doi.org/10.1109/tnnls.2016.2602365openalex-snapshot

Markov Blanket Feature Selection Using Representative Sets

inferred← citeshttps://doi.org/10.1142/s0219649222500095openalex-snapshot

DISSparse: Efficient Mining of Discriminative Itemsets

inferred← citeshttps://doi.org/10.1145/2700409openalex-snapshot

Classification with Streaming Features: An Emerging-Pattern Mining Approach

inferred← citeshttps://doi.org/10.1145/3106426.3106429openalex-snapshot

Efficient mining of discriminative itemsets

inferred← citeshttps://doi.org/10.32604/cmc.2022.026698openalex-snapshot

Interest Points Analysis for Internet Forum Based on Long-Short Windows Similarity

inferred← citeshttps://doi.org/10.48550/arxiv.1611.03977openalex-snapshot

A Review on Algorithms for Constraint-based Causal Discovery

inferred← citeshttps://doi.org/10.5204/thesis.eprints.120850openalex-snapshot

Mining Discriminative Itemsets in Data Streams Using Different Window Models

inferred← citeshttps://doi.org/10.5815/ijitcs.2016.02.02openalex-snapshot

Graph Models for Knowledge Representation and Reasoning for Contemporary and Emerging Needs – A Survey

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