26 papers · ranked by Valyu relevance
Yanchao Liu
This paper proposes a new mixed-integer programming (MIP) formulation to optimize split rule selection in the decision tree induction process, and develops an efficient search algorithm that is able to solve practical instances of the MIP model faster than commercial solvers. The formulation is novel for it directly…
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…
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…
Helen L. Smith, Patrick J. Biggs, Nigel P. French, Adam N. H. Smith + 1 more
To date, there remains no satisfactory solution for absent levels in random forest models. Absent levels are levels of a predictor variable encountered during prediction for which no explicit rule exists. Imposing an order on nominal predictors allows absent levels to be integrated and used for prediction. The ordering…
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…
Simultaneous Latent Budget Trees for Stratified Classification Cristian Buoncompagni, Stefano Pellegrino, Giulia Vannucci, Roberta Siciliano
In the era of Explainable Artificial Intelligence, there is a renewed focus on single trees for their ease of interpretation. This paper introduces Simultaneous Latent Budget Trees, a probabilistic machine learning framework for classification trees in the presence of a stratification factor such as a temporal…
Baojuan Yang
Most clothing recommendation methods have problems such as high resource consumption and inconsistent subjectively labeled clothing labels. Based on this, a multilabel classification algorithm based on deep learning (DL) theory is introduced, based on which the clothing style recognition model is constructed. Next, the…
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…
Jiancheng Tu, Wenqi Fan, Zhibin Wu
Rules Authors: ['Jiancheng Tu' 'Wenqi Fan' 'Zhibin Wu'] The global optimization of classification trees has demonstrated considerable promise, notably in enhancing accuracy, optimizing size, and thereby improving human comprehensibility. While existing optimal classification trees substantially enhance accuracy over…
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.…
Jonathan S. Kent, David H. Menager
For many years, researchers and practitioners have designed and employed rule-based classification systems. In contrast with other machine learning classifiers, rule-based systems are useful, not only because of their predictive power, but also because they often produce knowledge structures, or rules, humans readily…
Xi He, Max A. Little
In this paper, we introduce a generic data structure called decision trees, which integrates several well-known data structures, including binary search trees, -D trees, binary space partition trees, and decision tree models from machine learning. We provide the first axiomatic definition of decision trees. These…
Sergio Marconi, Ben. G. Weinstein, Sheng Zou, Stephanie A. Bohlman + 6 more
Advances in remote sensing imagery and computer vision applications unlock the potential for developing algorithms to classify individual trees from remote sensing at unprecedented scales. However, most approaches to date focus on site-specific applications and a small number of taxonomic groups. This limitation makes…
Aarav Arora, Igor Tsigelny, Valentina Kouznetsova
Purpose Laryngeal cancer (LC) is the most common head and neck cancer, which often goes undiagnosed due to the expensiveness and inaccessible nature of current diagnosis methods. Many recent studies have shown that microRNAs (miRNAs) are crucial biomarkers for a variety of cancers. Methods In this study, we create a…
Thomas A. Lake, Brit B. Laginhas, Brennen T. Farrell, Ross K. Meentemeyer + 1 more
Accurate and up-to-date catalogs of urban tree populations are crucial for quantifying ecosystem services and enhancing the quality of life in cities. However, identifying and mapping tree species cost-effectively remains a significant challenge. Remote sensing is an active area of research where scientists are…
Tom Hanika, Johannes Hirth
Random Forests and related tree-based methods are popular for supervised learning from table based data. Apart from their ease of parallelization, their classification performance is also superior. However, this performance, especially parallelizability, is offset by the loss of explainability. Statistical methods are…
Pablo del Moral, Sławomir Nowaczyk, Anita Sant’Anna, Sepideh Pashami
Using hierarchies of classes is one of the standard methods to solve multi-class classification problems. In the literature, selecting the right hierarchy is considered to play a key role in improving classification performance. Although different methods have been proposed, there is still a lack of understanding of…
Paul Kruse, Caroline Ring
This paper presents the treecompareR package for R, which provides tools for reproducible visualizations of data through the use of taxonomies. The package builds on developments from ggplot2 and ggtree to provide visualizations tailored for use with taxonomic classification data. Additionally, it provides tools that…
Jonas Schaub, Julian Zander, Achim Zielesny, Christoph Steinbeck
The concept of molecular scaffolds as defining core structures of organic molecules is utilised in many areas of chemistry and cheminformatics, e.g. drug design, chemical classification, or the analysis of high-throughput screening data. Here, we present Scaffold Generator, a comprehensive open library for the…
James G C Ball, Sadiq Jaffer, Anthony Laybros, Colin Prieur + 5 more
To understand how tropical rainforests will adapt to climate change and the extent to which their diversity imparts resilience, precise, taxonomically informed monitoring of individual trees is required. However, the density, diversity and complexity of tropical rainforests present considerable challenges to remote…
Prashanth Athri, Vidhya Murali, Pradyumna Y Muralidhar, Cassandra Königs + 4 more
- 1. Department of Computer Science and Engineering, Amrita School of Engineering, Amrita Vishwa Vidyapeetham, Bengaluru, India - 2. PES Center for Pattern Recognition, Department of Computer Science and Engineering, PES University, Bengaluru, India - 3. Bioinformatics and Medical Informatics, Bielefeld University…
Michael A. Zeller, Zebulun W. Arendsee, Gavin J.D. Smith, Tavis K. Anderson
Sequencing and phylogenetic classification have become a common task in human and animal diagnostic laboratories. It is routine to sequence pathogens to identify genetic variations of diagnostic significance and to use these data in real-time genomic contact tracing and surveillance. Under this paradigm, unprecedented…
Petr Novotný, Jan Wild
The unifying element of all biodiversity data is the issue of taxon hierarchy modeling. We compared 25 existing databases in terms of handling taxa hierarchy and presentation of this data. We used documentation or demo installations of databases as a source of information and next in line was the analysis of structures…
Vladimir Makarenkov, Gayane S. Barseghyan, Nadia Tahiri
Phylogenetic trees (i.e. evolutionary trees, additive trees or X-trees) play a key role in the processes of modeling and representing species evolution. Genome evolution of a given group of species is usually modeled by a species phylogenetic tree that represents the main patterns of vertical descent. However, the…
Sarah J. Graves, Sergio Marconi, Dylan Stewart, Ira Harmon + 14 more
Data on individual tree crowns from remote sensing have the potential to advance forest ecology by providing information about forest composition and structure with a continuous spatial coverage over large spatial extents. Classifying individual trees to their taxonomic species over large regions from remote sensing…
Authors not listed
SynTemp is a framework designed to extract and hierarchically cluster reaction templates from large-scale reaction data repositories. Reaction templates are partial Imaginary Transition State graphs representing the reaction center as well as surrounding context. These graphs are equivalent to Double Pushout graph…