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We report on a series of experiments in which all decision trees consistent with the training data are constructed. These experiments were run to gain an understanding of the properties of the set of consistent decision trees and the…

Artificial Intelligence · Computer Science 2008-02-03 P. M. Murphy , M. J. Pazzani

In order to speed-up classification models when facing a large number of categories, one usual approach consists in organizing the categories in a particular structure, this structure being then used as a way to speed-up the prediction…

Machine Learning · Computer Science 2015-11-26 Aurélia Léon , Ludovic Denoyer

In this paper we initiate the study of the forward and backward shifts on the Hardy space of a tree and the little Hardy space of a tree. In particular, we investigate when these shifts are bounded, find the norm of the shifts if they are…

Functional Analysis · Mathematics 2023-08-23 Adán Ángeles-Romero , Rubén A. Martínez Avendaño

Causal Bayesian Networks provide an important tool for reasoning under uncertainty with potential application to many complex causal systems. Structure learning algorithms that can tell us something about the causal structure of these…

Machine Learning · Computer Science 2024-04-15 Neville K Kitson , Anthony C Constantinou

We study the dynamics of an age-structured population in which the life expectancy of an offspring may be mutated with respect to that of its parent. When advantageous mutation is favored, the average fitness of the population grows…

Statistical Mechanics · Physics 2009-10-31 W. Hwang , P. L. Krapivsky , S. Redner

This article presents a new way to understand the descriptive ability of tree shape statistics. Where before tree shape statistics were chosen by their ability to distinguish between macroevolutionary models, the ``resolution'' presented in…

Populations and Evolution · Quantitative Biology 2007-05-23 Frederick A. Matsen

We construct a family of trees on which a lazy simple random walk exhibits total variation cutoff. The main idea behind the construction is that hitting times of large sets should be concentrated around their means. For this sequence of…

Probability · Mathematics 2013-07-11 Yuval Peres , Perla Sousi

Most genes are part of larger families of evolutionary related genes. The history of gene families typically involves duplications and losses of genes as well as horizontal transfers into other organisms. The reconstruction of detailed gene…

Populations and Evolution · Quantitative Biology 2023-04-25 Marc Hellmuth , Peter F. Stadler

Trees are fundamental data structure for many areas of computer science and system engineering. In this report, we show how to ensure eventual consistency of optimistically replicated trees. In optimistic replication, the different replicas…

Data Structures and Algorithms · Computer Science 2012-01-10 Stéphane Martin , Mehdi Ahmed-Nacer , Pascal Urso

Individuals do not respond uniformly to treatments, events, or interventions. Sociologists routinely partition samples into subgroups to explore how the effects of treatments vary by covariates like race, gender, and socioeconomic status.…

Other Statistics · Statistics 2019-09-23 Jennie E. Brand , Jiahui Xu , Bernard Koch , Pablo Geraldo

Binary rooted trees, both in the ordered and in the un-ordered case, are well studied structures in the field of combinatorics. The aim of this work is to study particular patterns in these classes of trees. We consider completely…

Combinatorics · Mathematics 2013-03-12 Filippo Disanto

This paper investigates the effects that perturbations to an optical system, such as translations or rotations of the optical elements, have on the final location where a light ray strikes a detector. Symmetry arguments are employed to give…

Physics Education · Physics 2007-05-23 Jason H. Steffen

We propose an innovative statistical method, called Ordinal Mixed-Effect Random Forest (OMERF), that extends the use of random forest to the analysis of hierarchical data and ordinal responses. The model preserves the flexibility and…

Methodology · Statistics 2024-06-06 Giulia Bergonzoli , Lidia Rossi , Chiara Masci

Many downstream applications are using dependency trees, and are thus relying on dependency parsers producing correct, or at least consistent, output. However, dependency parsers are trained using machine learning, and are therefore…

Computation and Language · Computer Science 2021-12-01 Dmytro Kalpakchi , Johan Boye

Latent tree analysis seeks to model the correlations among a set of random variables using a tree of latent variables. It was proposed as an improvement to latent class analysis --- a method widely used in social sciences and medicine to…

Machine Learning · Computer Science 2016-10-04 Nevin L. Zhang , Leonard K. M. Poon

We consider growing random recursive trees in random environment, in which at each step a new vertex is attached (by an edge of a random length) to an existing tree vertex according to a probability distribution that assigns the tree…

Probability · Mathematics 2007-05-23 Konstantin Borovkov , Vladimir Vatutin

Phylogenetic mixture models are statistical models of character evolution allowing for heterogeneity. Each of the classes in some unknown partition of the characters may evolve by different processes, or even along different trees. The…

Populations and Evolution · Quantitative Biology 2010-11-19 John A. Rhodes , Seth Sullivant

In this paper, we study the induced homological sequence and the induced merge tree of a discrete Morse function on a tree. A discrete Morse function on a tree gives rise to a sequence of Betti numbers that keep track of the number of…

General Mathematics · Mathematics 2024-10-31 Nicholas A. Scoville , Dylan Wen

The premise of genetic analysis is that a causal link exists between phenotypic and allelic variation. Yet it has long been documented that mutant phenotypes are not a simple result of a single DNA lesion, but rather are due to interactions…

Genomics · Quantitative Biology 2014-06-04 Chris H. Chandler , Sudarshan Chari , Ian Dworkin

In this paper we find the generating function for the number of vertices which have $k$ elements in their subtree and use this generating function to calculate the probability that a vertex has a size $k$ subtree. We also show how this same…

Combinatorics · Mathematics 2019-04-12 Anthony Van Duzer