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The construction of efficient and effective decision trees remains a key topic in machine learning because of their simplicity and flexibility. A lot of heuristic algorithms have been proposed to construct near-optimal decision trees. ID3,…

Machine Learning · Statistics 2016-08-24 Yisen Wang , Chaobing Song , Shu-Tao Xia

Decision Tree is a well understood Machine Learning model that is based on minimizing impurities in the internal nodes. The most common impurity measures are Shannon entropy and Gini impurity. These impurity measures are insensitive to the…

Machine Learning · Computer Science 2024-06-03 Harikrishnan N B , Arham Jain , Nithin Nagaraj

Recently, weighted cumulative residual Tsallis entropy has been introduced in the literature as a generalization of weighted cumulative residual entropy. We study some new properties of weighted cumulative residual Tsallis entropy measure.…

Statistics Theory · Mathematics 2026-02-02 Siddhartha Chakraborty , Asok K. Nanda

The coupled entropy is proven to correct a flaw in the derivation of the Tsallis entropy and thereby solidify the theoretical foundations for analyzing the uncertainty of complex systems. The Tsallis entropy originated from considering…

Machine Learning · Statistics 2025-11-25 Kenric P. Nelson

An impurity measures $I: \mathbb{R}^d \mapsto \mathbb{R}^+$ is a function that assigns a $d$-dimensional vector ${\bf v}$ to a non-negative value $I({\bf v})$ so that the more homogeneous ${\bf v}$, with respect to the values of its…

Data Structures and Algorithms · Computer Science 2019-11-19 Ferdinando Cicalese , Eduardo Laber

Decision trees are popular classification models, providing high accuracy and intuitive explanations. However, as the tree size grows the model interpretability deteriorates. Traditional tree-induction algorithms, such as C4.5 and CART,…

Machine Learning · Computer Science 2022-11-29 Guangyi Zhang , Aristides Gionis

Optimal transport is a powerful framework for computing distances between probability distributions. We unify the two main approaches to optimal transport, namely Monge-Kantorovitch and Sinkhorn-Cuturi, into what we define as Tsallis…

Machine Learning · Computer Science 2016-09-16 Boris Muzellec , Richard Nock , Giorgio Patrini , Frank Nielsen

Coherence is the most fundamental quantum feature of the nonclassical systems. The understanding of coherence within the resource theory has been attracting increasing interest among which the quantification of coherence is an essential…

Quantum Physics · Physics 2018-01-16 Haiqing Zhao , Chang-shui Yu

Thinking Large Language Models (LLMs) used as judges for pairwise preferences remain noisy at the single-sample level, and common aggregation rules (majority vote, soft self-consistency, or instruction-based self-aggregation) are…

Machine Learning · Computer Science 2025-12-03 Hamid Dadkhahi , Firas Trabelsi , Parker Riley , Juraj Juraska , Mehdi Mirzazadeh

Mechanistic interpretability has identified functional subgraphs within large language models (LLMs), known as Transformer Circuits (TCs), that appear to implement specific algorithms. Yet we lack a formal, single-pass way to quantify when…

Machine Learning · Computer Science 2026-04-07 Anatoly A. Krasnovsky

Background. The reliability paradox describes the empirical observation that cognitive tasks producing robust group-level effects often yield poor between-individual reliability. Existing approaches rely predominantly on the intraclass…

Methodology · Statistics 2026-05-26 Maria Westrin

Integrated Information Theory (IIT) is a prominent theory of consciousness that has at its centre measures that quantify the extent to which a system generates more information than the sum of its parts. While several candidate measures of…

Neurons and Cognition · Quantitative Biology 2019-01-30 Pedro A. M. Mediano , Anil K. Seth , Adam B. Barrett

This paper introduces a novel formulation of the clustering problem, namely the Minimum Sum-of-Squares Clustering of Infinitely Tall Data (MSSC-ITD), and presents HPClust, an innovative set of hybrid parallel approaches for its effective…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-06-26 Ravil Mussabayev , Rustam Mussabayev

In this paper, we provide a generalized framework for Variational Inference-Stochastic Optimal Control by using thenon-extensive Tsallis divergence. By incorporating the deformed exponential function into the optimality likelihood function,…

Machine Learning · Computer Science 2021-04-02 Ziyi Wang , Oswin So , Jason Gibson , Bogdan Vlahov , Manan S. Gandhi , Guan-Horng Liu , Evangelos A. Theodorou

In this work we examine two different measures for inhomogeneity and complexity that are derived from nonextensive considerations a' la Tsallis. Their performance is then tested on theoretically generated patterns. All measures are found to…

Statistical Mechanics · Physics 2009-11-07 R. Piasecki , M. T. Martin , A. Plastino

InteGriTy is a software package that performs topological analysis following AIM approach on electron densities given on 3D grids. Use of tricubic interpolation is made to get the density, its gradient and hessian matrix at any required…

Chemical Physics · Physics 2007-05-23 C. Katan , P. Rabiller , C. Lecomte , M. Guezo , V. Oison , M. Souhassou

The Half-Trek Criterion (HTC) is the primary graphical tool for determining generic identifiability of causal effect coefficients in linear structural equation models (SEMs) with latent confounders. However, HTC is inherently node-wise: it…

Machine Learning · Statistics 2026-04-13 Ziyi Ding , Xiao-Ping Zhang

We present a systematically improvable tensor hypercontraction (THC) factorization based on interpolative separable density fitting (ISDF). We illustrate algorithmic details to achieve this within the framework of Becke's atom-centered…

Chemical Physics · Physics 2020-01-15 Joonho Lee , Lin Lin , Martin Head-Gordon

The primary purpose of the collective Thomson scattering (CTS) diagnostic at ITER is to measure the properties of fast-ion populations, in particular those of fusion-born $\alpha$-particles. Based on the present design of the diagnostic, we…

Quantifying coherence is an essential endeavor for both quantum mechanical foundations and quantum technologies. We present a bona fide measure of quantum coherence by utilizing the Tsallis relative operator $(\alpha, \beta)$-entropy. We…

Quantum Physics · Physics 2023-06-22 Meng-Li Guo , Zhi-Xiang Jin , Jin-Min Liang , Bo Li , Shao-Ming Fei
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