Results 131 to 140 of about 452,858 (310)

Monocular Road Detection Using Structured Random Forest

International Journal of Advanced Robotic Systems, 2016
Road detection is a key task for autonomous land vehicles. Monocular vision-based road-detection algorithms are mostly based on machine learning approaches and are usually cast as classification problems.
Liang Xiao, Bin Dai, Daxue Liu, Dawei Zhao, Tao Wu   +4 more
doaj   +1 more source

DPRF: A Differential Privacy Protection Random Forest

IEEE Access, 2019
Providing privacy protection for classification algorithms has become a research hotspot in current data mining. In this paper, differential privacy is applied to the random forest classification algorithm, and a random forest algorithm based on ...
Jun Hou, Qianmu Li, Shunmei Meng, Zhen Ni, Yini Chen, Yaozong Liu   +5 more
doaj   +1 more source

Random Forests for Multiclass Classification: Random

, 2008
—Several supervised learning algorithms are suited to classify instances into a multiclass value space. MultiNomial Logit (MNL) is recognized as a robust classifier and is commonly applied within the CRM (Customer Relationship Management) domain ...
Multinomial Logit, Random Multinomial Logit   +1 more
core  

Meta random forest : random forest with simple random forest as base model

, 2020
The abundance of data along with the significant rise of computational power boost the popularity and usage of machine learning in recent decision making and forecasting.
Kurniawan, Billy
core  

3D Printing Innovations in Polymeric Porous and Patterned Architecture

Advanced Functional Materials, EarlyView.
Polymeric foams occupy a unique structural space between dense solids and open networks, where engineered void fraction governs mechanical compliance, thermal resistance, and mass transport. Additive manufacturing now enables precise spatial control over cellular architecture, unlocking designer foam structures across applications spanning crash ...
Dhanush Patil, Sri Vaishnavi Thummalapalli, Clarissa Westover, Arunachalam Ramanathan, M. Taylor Sobzcak, Roumika Patil, Qixuan Xiang, Tiantian Li, Sui Yang, Timothy E. Long, Hongyue Sun, Xianqiao Wang, Yang Liu, Kenan Song   +13 more
wiley   +1 more source

Calibrating Random Forests

2008 Seventh International Conference on Machine Learning and Applications, 2008
When using the output of classifiers to calculate the expected utility of different alternatives in decision situations, the correctness of predicted class probabilities may be of crucial importance. However, even very accurate classifiers may output class probabilities of rather poor quality.
openaire   +3 more sources

Dynamic Interfacial Chemistry of Choline Chloride as Electrolyte Additive for Stable Zn‐Iodine Batteries

Advanced Functional Materials, EarlyView.
Choline chloride (ChCl) additive enables dynamic interface engineering in Zn‐I2 batteries by forming hydrophobic polyiodide complexes and a Zn‐stabilizing Ch+‐rich layer under electric field modulation. This dual‐function strategy suppresses iodine hydrolysis and dendrite formation, while optimizing Zn2+ solvation and transport for high‐efficiency ...
Xiaoyu Bi, Yuchuan Ren, Ao Yu, Linlin Yang, Ren He, Yapeng Cheng, Xingqi Chang, Xuan Lu, Yanting Xie, Qian Xue, Hu Yuan, Canhuang Li, Runzhou Huang, Jordi Jacas Biendicho, Chaoqi Zhang, Jian Shang, Andreu Cabot   +16 more
wiley   +1 more source

Ultrasmall High‐Entropy Materials: Nanoscale Effects, Synthesis, and Mechanistic Insights

Advanced Functional Materials, EarlyView.
This review article focuses on sub‐10 nm high‐entropy materials that combine nanoscale design with complex compositions for next‐generation applications. ABSTRACT Ultrasmall high‐entropy nanomaterials (USHENMs, <10 nm) merge multicomponent chemistry with size‐dependent effects, forming a distinct class of materials with unprecedented properties.
Yueyue He, Wenbo Wang, Simon Schweidler, Yanjiao Ma, Ben Breitung, Torsten Brezesinski   +5 more
wiley   +1 more source

Standardized Effect Measures Informing Next‐Generation Strategies for Mechanical Stimulation in Cartilage Tissue Engineering

Advanced Healthcare Materials, EarlyView.
This systematic review quantitatively compares conventional mechanical stimulation strategies in cartilage tissue engineering across 85 heterogeneous in vitro studies. Applying standardized effect measures, meta‐analysis reveals that combined compression and shear loading optimally promotes cartilage matrix development.
Jiaqi K. Shen, Tony B. Huang, Catherine E. Davey, Elias Salzer, Gerjo J. V. M. Van Osch, Sandra J. Shefelbine, Marcus G. Pandy, Kathryn S. Stok   +7 more
wiley   +1 more source

Comparison of oblique random survival forest, random survival forest, and statistical models for time-to-event data using simulation study

Scientific Reports
Time-to-event (TTE) machine learning (ML) algorithms are increasingly utilized in prognostic models, but systematic evaluation is lacking to identify their strengths and limitations.
Abubaker Suliman, Aminu S. Abdullahi, Mohammad Mehedy Masud, Mohamed Adel Serhani, Amal AlZahmi, Abderrahim Oulhaj   +5 more
doaj   +1 more source