Results 51 to 60 of about 85,077 (292)
Adversarial attacks against supervised machine learning based network intrusion detection systems.
PLoS ONE, 2022 Adversarial machine learning is a recent area of study that explores both adversarial attack strategy and detection systems of adversarial attacks, which are inputs specially crafted to outwit the classification of detection systems or disrupt the ...
Ebtihaj Alshahrani +3 more
doaj +2 more sources
Active Learning Embedded in Incremental Decision Trees
, 2020 As technology evolves and electronic devices become widespread, the amount of data produced in the form of stream increases in enormous proportions. Data streams are an online source of data, meaning that it keeps producing data continuously. This creates the need for fast and reliable methods to analyse and extract information from these sources ...
Vinicius Eiji Martins +2 more
openaire +2 more sources
Hyperparameter Optimization Using Iterative Decision Tree (IDT)
IEEE Access, 2022 Machine learning and deep learning have gained a lot of attention from researchers because of their promising predictive performance and the availability of extensive high-dimensional data and high-performance computational hardware.
Narith Saum +2 more
doaj +1 more source
Molecular Oncology, EarlyView.Large multidimensional digital images of cancer tissue are becoming prolific, but many challenges exist to automatically extract relevant information from them using computational tools. We describe publicly available resources that have been developed jointly by expert and non‐expert computational biologists working together during a virtual hackathon
Sandhya Prabhakaran +16 more
wiley +1 more source
Learning Binary Decision Trees by Argmin Differentiation
, 2020 We address the problem of learning binary decision trees that partition data for some downstream task. We propose to learn discrete parameters (i.e., for tree traversals and node pruning) and continuous parameters (i.e., for tree split functions and prediction functions) simultaneously using argmin differentiation. We do so by sparsely relaxing a mixed-
Zantedeschi, Valentina +2 more
openaire +2 more sources
Learning decision trees from random examples
Information and Computation, 1989 AbstractWe define the rank of a decision tree and show that for any fixed r, the class of all decision trees of rank at most r on n Boolean variables is learnable from random examples in time polynomial in n and linear in 1/ɛ and log(1/δ), where ɛ is the accuracy parameter and δ is the confidence parameter.
A. Ehrenfeucht +2 more
openaire +3 more sources
Archives of Academic Emergency Medicine, 2021 Introduction: The use of computed tomography (CT) scan is essential for making diagnoses for trauma patients in emergency medicine. Numerous studies have been conducted on guiding medical examinations in light of advances in machine learning, leading to ...
Mohsen Shahverdy, Hamed Malek
doaj +1 more source
Bridging Nature and Technology: A Perspective on Role of Machine Learning in Bioinspired Ceramics
Advanced Engineering Materials, EarlyView.Machine learning (ML) is revolutionizing the development of bioinspired ceramics. This article investigates how ML can be used to design new ceramic materials with exceptional performance, inspired by the structures found in nature. The research highlights how ML can predict material properties, optimize designs, and create advanced models to unlock a ...
Hamidreza Yazdani Sarvestani +2 more
wiley +1 more source
Lower bounds on learning decision lists and trees
Information and Computation, 1995 Abstractk-Decision lists and decision trees play important roles in learning theory as well as in practical learning systems.k-Decision lists generalize classes such as monomials,k-DNF, andk-CNF, and like these subclasses they are polynomially PAC-learnable [R. Rivest,Mach. Learning2(1987), 229–246].
Ming Li +3 more
openaire +3 more sources
Decision Tree-Based Ensemble Model for Predicting National Greenhouse Gas Emissions in Saudi Arabia
Applied Sciences, 2023 Greenhouse gas (GHG) emissions must be precisely estimated in order to predict climate change and achieve environmental sustainability in a country.
Muhammad Muhitur Rahman +7 more
doaj +1 more source