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16 papers · ranked by Valyu relevance

01
PPubMed31 May 2025
Methodological Review of Classification Trees for Risk Stratification: An Application Example in the Obesity Paradox
Javier Trujillano, Luis Serviá, Mariona Badia, José C. E. Serrano + 8 more
'María Luisa Bordejé-Laguna' 'Carol Lorencio' 'Clara Vaquerizo' 'José Luis Flordelis-Lasierra' 'Itziar Martínez de Lagrán' 'Esther Portugal-Rodríguez' 'Juan Carlos López-Delgado' 'Annunziata Lapolla'] Background: Classification trees (CTs) are widely used machine learning algorithms with growing applications in…
88relevance
02
PPubMed30 Mar 2012
Comprehensive Decision Tree Models in Bioinformatics Comprehensive Decision Tree Models
Gregor Stiglic, Simon Kocbek, Igor Pernek, Peter Kokol + 1 more
'Ahmed Moustafa'] Purpose Classification is an important and widely used machine learning technique in bioinformatics. Researchers and other end-users of machine learning software often prefer to work with comprehensible models where knowledge extraction and explanation of reasoning behind the classification model are…
84relevance
03
PPubMed18 Apr 2024
<i> ITree </i> : a user-driven tool for interactive decision-making with classification trees
Hubert Sokołowski, Marcin Czajkowski, Anna Czajkowska, Krzysztof Jurczuk + 2 more
The ITree tool allows us to fully control the output of the Decision Tree (DT), its structure, as well as the induction process. In [btae273-F1], we present the main view of the ITree website, while the rest of the elements (C-E) are dialog windows that may appear based on user activity. At the top of the ITree website…
83relevance
04
PPubMed14 Dec 2021
Minimum Query Set for Decision Tree Construction
Wojciech Wieczorek, Jan Kozak, Łukasz Strąk, Arkadiusz Nowakowski + 1 more
A new two-stage method for the construction of a decision tree is developed. The first stage is based on the definition of a minimum query set, which is the smallest set of attribute-value pairs for which any two objects can be distinguished. To obtain this set, an appropriate linear programming model is proposed. The…
82relevance
05
PPubMed13 Dec 2020
Classification of Biodegradable Substances Using Balanced Random Trees and Boosted C5.0 Decision Trees
Alaa M. Elsayad, Ahmed M. Nassef, Mujahed Al-Dhaifallah, Khaled A. Elsayad
'Khaled A. Elsayad'] Substances that do not degrade over time have proven to be harmful to the environment and are dangerous to living organisms. Being able to predict the biodegradability of substances without costly experiments is useful. Recently, the quantitative structure-activity relationship (QSAR) models have…
82relevance
06
PPubMed26 Jul 2023
Decision trees: from efficient prediction to responsible AI
Hendrik Blockeel, Laurens Devos, Benoît Frénay, Géraldin Nanfack + 1 more
'Siegfried Nijssen'] This article provides a birds-eye view on the role of decision trees in machine learning and data science over roughly four decades. It sketches the evolution of decision tree research over the years, describes the broader context in which the research is situated, and summarizes strengths and…
81relevance
07
PPubMed7 Aug 2013
Categorizing Ideas about Trees: A Tree of Trees Categorizing Ideas about Trees: A Tree of Trees
Marie Fisler, Guillaume Lecointre, Simon Joly
The aim of this study is to explore whether matrices and MP trees used to produce systematic categories of organisms could be useful to produce categories of ideas in history of science. We study the history of the use of trees in systematics to represent the diversity of life from 1766 to 1991. We apply to those ideas…
79relevance
08
PPubMed7 Feb 2024
Ensemble methods of rank-based trees for single sample classification with gene expression profiles
Min Lu, Ruijie Yin, X. Steven Chen
Building Single Sample Predictors (SSPs) from gene expression profiles presents challenges, notably due to the lack of calibration across diverse gene expression measurement technologies. However, recent research indicates the viability of classifying phenotypes based on the order of expression of multiple genes.…
78relevance
09
PPubMed20 Dec 2013
A new approach to enhance the performance of decision tree for classifying gene expression data
Md Rafiul Hassan, Ramamohanarao Kotagiri
Background Gene expression data classification is a challenging task due to the large dimensionality and very small number of samples. Decision tree is one of the popular machine learning approaches to address such classification problems. However, the existing decision tree algorithms use a single gene feature at each…
77relevance
10
PPubMed20 Jan 2018
L-Tree: A Local-Area-Learning-Based Tree Induction Algorithm for Image Classification
Jaesung Choi, Eungyeol Song, Sangyoun Lee
The decision tree is one of the most effective tools for deriving meaningful outcomes from image data acquired from the visual sensors. Owing to its reliability, superior generalization abilities, and easy implementation, the tree model has been widely used in various applications. However, in image classification…
76relevance
11
PPubMed15 Oct 2021
Hypertension-Related Drug Activity Identification Based on Novel Ensemble Method Yang et al. Hypertension-Related Drug Activity Identification
Bin Yang, Wenzheng Bao, Jinglong Wang
Hypertension is a chronic disease and major risk factor for cardiovascular and cerebrovascular diseases that often leads to damage to target organs. The prevention and treatment of hypertension is crucially important for human health. In this paper, a novel ensemble method based on a flexible neural tree (FNT) is…
76relevance
12
PPubMed20 Feb 2018
Recruiting Conventional Tree Architecture Models into State-of-the-Art LiDAR Mapping for Investigating Tree Growth Habits in Structure
Yi Lin, Miao Jiang, Petri Pellikka, Janne Heiskanen
Mensuration of tree growth habits is of considerable importance for understanding forest ecosystem processes and forest biophysical responses to climate changes. However, the complexity of tree crown morphology that is typically formed after many years of growth tends to render it a non-trivial task, even for the…
72relevance
13
PPubMed22 Feb 2020
Using Domain Knowledge for Interpretable and Competitive Multi-Class Human Activity Recognition
Sebastian Scheurer, Salvatore Tedesco, Kenneth N. Brown, Brendan O’Flynn
'Brendan O’Flynn'] Human activity recognition (HAR) has become an increasingly popular application of machine learning across a range of domains. Typically the HAR task that a machine learning algorithm is trained for requires separating multiple activities such as walking, running, sitting, and falling from each…
71relevance
14
PPubMed21 Jun 2018
Deciding on the Starting Number of Classes of a Latent Class Tree
Mattis van den Bergh, Geert H. van Kollenburg, Jeroen K. Vermunt
In recent studies, latent class tree (LCT) modeling has been proposed as a convenient alternative to standard latent class (LC) analysis. Instead of using an estimation method in which all classes are formed simultaneously given the specified number of classes, in LCT analysis a hierarchical structure of mutually…
70relevance
15
PPubMed19 Dec 2019
A hierarchical loss and its problems when classifying non-hierarchically A hierarchical loss and its problems when classifying non-hierarchically
Cinna Wu, Mark Tygert, Yann LeCun, Friedhelm Schwenker
Failing to distinguish between a sheepdog and a skyscraper should be worse and penalized more than failing to distinguish between a sheepdog and a poodle; after all, sheepdogs and poodles are both breeds of dogs. However, existing metrics of failure (so-called “loss” or “win”) used in textual or visual…
69relevance
16
PPubMed30 Jan 2010
From learning taxonomies to phylogenetic learning: Integration of 16S rRNA gene data into FAME-based bacterial classification
Bram Slabbinck, Willem Waegeman, Peter Dawyndt, Paul De Vos + 1 more
'Bernard De Baets'] Background Machine learning techniques have shown to improve bacterial species classification based on fatty acid methyl ester (FAME) data. Nonetheless, FAME analysis has a limited resolution for discrimination of bacteria at the species level. In this paper, we approach the species classification…
67relevance

Results for Classification trees

Methodological Review of Classification Trees for Risk Stratification: An Application Example in the Obesity Paradox

Comprehensive Decision Tree Models in Bioinformatics Comprehensive Decision Tree Models

<i> ITree </i> : a user-driven tool for interactive decision-making with classification trees

Minimum Query Set for Decision Tree Construction

Classification of Biodegradable Substances Using Balanced Random Trees and Boosted C5.0 Decision Trees

Decision trees: from efficient prediction to responsible AI

Categorizing Ideas about Trees: A Tree of Trees Categorizing Ideas about Trees: A Tree of Trees

Ensemble methods of rank-based trees for single sample classification with gene expression profiles

A new approach to enhance the performance of decision tree for classifying gene expression data

L-Tree: A Local-Area-Learning-Based Tree Induction Algorithm for Image Classification

Hypertension-Related Drug Activity Identification Based on Novel Ensemble Method Yang et al. Hypertension-Related Drug Activity Identification

Recruiting Conventional Tree Architecture Models into State-of-the-Art LiDAR Mapping for Investigating Tree Growth Habits in Structure

Using Domain Knowledge for Interpretable and Competitive Multi-Class Human Activity Recognition

Deciding on the Starting Number of Classes of a Latent Class Tree

A hierarchical loss and its problems when classifying non-hierarchically A hierarchical loss and its problems when classifying non-hierarchically

From learning taxonomies to phylogenetic learning: Integration of 16S rRNA gene data into FAME-based bacterial classification

Methodological Review of Classification Trees for Risk Stratification: An Application Example in the Obesity Paradox

Comprehensive Decision Tree Models in Bioinformatics Comprehensive Decision Tree Models

<i> ITree </i> : a user-driven tool for interactive decision-making with classification trees

Minimum Query Set for Decision Tree Construction

Classification of Biodegradable Substances Using Balanced Random Trees and Boosted C5.0 Decision Trees

Decision trees: from efficient prediction to responsible AI

Categorizing Ideas about Trees: A Tree of Trees Categorizing Ideas about Trees: A Tree of Trees

Ensemble methods of rank-based trees for single sample classification with gene expression profiles

A new approach to enhance the performance of decision tree for classifying gene expression data

L-Tree: A Local-Area-Learning-Based Tree Induction Algorithm for Image Classification

Hypertension-Related Drug Activity Identification Based on Novel Ensemble Method Yang et al. Hypertension-Related Drug Activity Identification

Recruiting Conventional Tree Architecture Models into State-of-the-Art LiDAR Mapping for Investigating Tree Growth Habits in Structure

Using Domain Knowledge for Interpretable and Competitive Multi-Class Human Activity Recognition

Deciding on the Starting Number of Classes of a Latent Class Tree

A hierarchical loss and its problems when classifying non-hierarchically A hierarchical loss and its problems when classifying non-hierarchically

From learning taxonomies to phylogenetic learning: Integration of 16S rRNA gene data into FAME-based bacterial classification