Advances in Data Analysis and Classification

Papers
(The TQCC of Advances in Data Analysis and Classification is 3. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2020-05-01 to 2024-05-01.)
ArticleCitations
A comparison of instance-level counterfactual explanation algorithms for behavioral and textual data: SEDC, LIME-C and SHAP-C42
Is there a role for statistics in artificial intelligence?27
Robust archetypoids for anomaly detection in big functional data15
Minimum adjusted Rand index for two clusterings of a given size12
An empirical comparison and characterisation of nine popular clustering methods11
Notes on the H-measure of classifier performance10
The GNG neural network in analyzing consumer behaviour patterns: empirical research on a purchasing behaviour processes realized by the elderly consumers10
Gaussian mixture modeling and model-based clustering under measurement inconsistency9
PCA-KL: a parametric dimensionality reduction approach for unsupervised metric learning9
Editable machine learning models? A rule-based framework for user studies of explainability9
Assessing similarities between spatial point patterns with a Siamese neural network discriminant model8
Robust logistic zero-sum regression for microbiome compositional data8
Learning multivariate shapelets with multi-layer neural networks for interpretable time-series classification8
Hierarchical clustering with discrete latent variable models and the integrated classification likelihood8
Multivariate cluster weighted models using skewed distributions8
Adaptive sparse group LASSO in quantile regression7
Clustering discrete-valued time series7
Robust optimal classification trees under noisy labels7
Mixtures of Dirichlet-Multinomial distributions for supervised and unsupervised classification of short text data7
Robust clustering via mixtures of t factor analyzers with incomplete data6
The ultrametric correlation matrix for modelling hierarchical latent concepts6
Functional data clustering by projection into latent generalized hyperbolic subspaces6
Mixtures of factor analyzers with scale mixtures of fundamental skew normal distributions6
Data generation for composite-based structural equation modeling methods6
New models for symbolic data analysis6
Mixed Deep Gaussian Mixture Model: a clustering model for mixed datasets6
Basis expansion approaches for functional analysis of variance with repeated measures5
Robust semiparametric inference for polytomous logistic regression with complex survey design5
Active learning of constraints for weighted feature selection5
Model-based clustering and outlier detection with missing data5
M-estimators and trimmed means: from Hilbert-valued to fuzzy set-valued data5
Automatic gait classification patterns in spastic hemiplegia5
How many data clusters are in the Galaxy data set?5
The minimum weighted covariance determinant estimator for high-dimensional data5
Clustering of modal-valued symbolic data5
Finite mixture modeling of censored and missing data using the multivariate skew-normal distribution5
Hierarchical conceptual clustering based on quantile method for identifying microscopic details in distributional data4
ParticleMDI: particle Monte Carlo methods for the cluster analysis of multiple datasets with applications to cancer subtype identification4
A new three-step method for using inverse propensity weighting with latent class analysis4
Nonparametric estimation of directional highest density regions4
Consensus among preference rankings: a new weighted correlation coefficient for linear and weak orderings4
Estimating the class prior for positive and unlabelled data via logistic regression4
Are attitudes toward immigration changing in Europe? An analysis based on latent class IRT models4
Model-based clustering for random hypergraphs4
A novel dictionary learning method based on total least squares approach with application in high dimensional biological data4
A bias-variance analysis of state-of-the-art random forest text classifiers4
Gaussian mixture model with an extended ultrametric covariance structure4
Benchmarking distance-based partitioning methods for mixed-type data3
Sparse group fused lasso for model segmentation: a hybrid approach3
Sparse correspondence analysis for large contingency tables3
Mining maximal frequent rectangles3
Strong consistency of the MLE under two-parameter Gamma mixture models with a structural scale parameter3
Predicting brand confusion in imagery markets based on deep learning of visual advertisement content3
A stochastic block model for interaction lengths3
On discriminating between lognormal and Pareto tail: an unsupervised mixture-based approach3
Robust mixture regression modeling based on two-piece scale mixtures of normal distributions3
Sparse dimension reduction based on energy and ball statistics3
Better than the best? Answers via model ensemble in density-based clustering3
Quantile composite-based path modeling: algorithms, properties and applications3
Classification based on multivariate mixed type longitudinal data with an application to the EU-SILC database3
LASSO regularization within the LocalGLMnet architecture3
Regime dependent interconnectedness among fuzzy clusters of financial time series3
Robust regression with compositional covariates including cellwise outliers3
Over-optimistic evaluation and reporting of novel cluster algorithms: an illustrative study3
Detecting and classifying outliers in big functional data3
Threshold-based Naïve Bayes classifier3
On the use of quantile regression to deal with heterogeneity: the case of multi-block data3
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