Search Results - "Advances in data analysis and classification"

A computationally fast variable importance test for random forests for high-dimensional data by Janitza, Silke, Celik, Ender, Boulesteix, Anne-Laure

“…Random forests are a commonly used tool for classification and for ranking candidate predictors based on the so-called variable importance measures. These…”
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Functional data clustering: a survey by Jacques, Julien, Preda, Cristian

“…Clustering techniques for functional data are reviewed. Four groups of clustering algorithms for functional data are proposed. The first group consists of…”
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A comparison of instance-level counterfactual explanation algorithms for behavioral and textual data: SEDC, LIME-C and SHAP-C by Ramon, Yanou, Martens, David, Provost, Foster, Evgeniou, Theodoros

“…Predictive systems based on high-dimensional behavioral and textual data have serious comprehensibility and transparency issues: linear models require…”
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A novel method for forecasting time series based on fuzzy logic and visibility graph by Zhang, Rong, Ashuri, Baabak, Deng, Yong

“…Time series attracts much attention for its remarkable forecasting potential. This paper discusses how fuzzy logic improves accuracy when forecasting time…”
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Greedy Gaussian segmentation of multivariate time series by Hallac, David, Nystrup, Peter, Boyd, Stephen

“…We consider the problem of breaking a multivariate (vector) time series into segments over which the data is well explained as independent samples from a…”
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Ensemble of optimal trees, random forest and random projection ensemble classification by Khan, Zardad, Gul, Asma, Perperoglou, Aris, Miftahuddin, Miftahuddin, Mahmoud, Osama, Adler, Werner, Lausen, Berthold

“…The predictive performance of a random forest ensemble is highly associated with the strength of individual trees and their diversity. Ensemble of a small…”
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A two-stage sparse logistic regression for optimal gene selection in high-dimensional microarray data classification by Algamal, Zakariya Yahya, Lee, Muhammad Hisyam

“…The common issues of high-dimensional gene expression data are that many of the genes may not be relevant, and there exists a high correlation among genes…”
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From here to infinity: sparse finite versus Dirichlet process mixtures in model-based clustering by Frühwirth-Schnatter, Sylvia, Malsiner-Walli, Gertraud

“…In model-based clustering mixture models are used to group data points into clusters. A useful concept introduced for Gaussian mixtures by Malsiner Walli et…”
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Is there a role for statistics in artificial intelligence? by Friedrich, Sarah, Antes, Gerd, Behr, Sigrid, Binder, Harald, Brannath, Werner, Dumpert, Florian, Ickstadt, Katja, Kestler, Hans A., Lederer, Johannes, Leitgöb, Heinz, Pauly, Markus, Steland, Ansgar, Wilhelm, Adalbert, Friede, Tim

“…The research on and application of artificial intelligence (AI) has triggered a comprehensive scientific, economic, social and political discussion. Here we…”
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Ensemble feature selection for high dimensional data: a new method and a comparative study by Ben Brahim, Afef, Limam, Mohamed

“…The curse of dimensionality is based on the fact that high dimensional data is often difficult to work with. A large number of features can increase the noise…”
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Ensemble of a subset of kNN classifiers by Gul, Asma, Perperoglou, Aris, Khan, Zardad, Mahmoud, Osama, Miftahuddin, Miftahuddin, Adler, Werner, Lausen, Berthold

“…Combining multiple classifiers, known as ensemble methods, can give substantial improvement in prediction performance of learning algorithms especially in the…”
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Minimum adjusted Rand index for two clusterings of a given size by Chacón, José E., Rastrojo, Ana I.

“…The adjusted Rand index (ARI) is commonly used in cluster analysis to measure the degree of agreement between two data partitions. Since its introduction,…”
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On mixtures of skew normal and skew $$t$$ -distributions by Lee, Sharon X., McLachlan, Geoffrey J.

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Threshold-based Naïve Bayes classifier by Romano, Maurizio, Contu, Giulia, Mola, Francesco, Conversano, Claudio

“…The Threshold-based Naïve Bayes (Tb-NB) classifier is introduced as a (simple) improved version of the original Naïve Bayes classifier. Tb-NB extracts the…”
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A principal component method to impute missing values for mixed data by Audigier, Vincent, Husson, François, Josse, Julie

“…We propose a new method to impute missing values in mixed data sets. It is based on a principal component method, the factorial analysis for mixed data, which…”
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On discriminating between lognormal and Pareto tail: an unsupervised mixture-based approach by Bee, Marco

“…Many stochastic models in economics and finance are described by distributions with a lognormal body. Testing for a possible Pareto tail and estimating the…”
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Identification of representative trees in random forests based on a new tree-based distance measure by Laabs, Björn-Hergen, Westenberger, Ana, König, Inke R.

“…In life sciences, random forests are often used to train predictive models. However, gaining any explanatory insight into the mechanics leading to a specific…”
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Composite likelihood methods for parsimonious model-based clustering of mixed-type data by Ranalli, Monia, Rocci, Roberto

“…In this paper, we propose twelve parsimonious models for clustering mixed-type (ordinal and continuous) data. The dependence among the different types of…”
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RGA: a unified measure of predictive accuracy by Giudici, Paolo, Raffinetti, Emanuela

“…Abstract A key point to assess statistical forecasts is the evaluation of their predictive accuracy. Recently, a new measure, called Rank Graduation Accuracy…”
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Notes on the H-measure of classifier performance by Hand, D. J., Anagnostopoulos, C.

“…The H-measure is a classifier performance measure which takes into account the context of application without requiring a rigid value of relative…”
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