Results 101 to 110 of about 1,169,808 (377)
Learning Decision Trees for Unbalanced Data [PDF]
, 2008 Learning from unbalanced datasets presents a convoluted problem in which traditional learning algorithms may perform poorly. The objective functions used for learning the classifiers typically tend to favor the larger, less important classes in such problems.
David A. Cieslak, Nitesh V. Chawla
openaire +2 more sources
, 2019 One obstacle that so far prevents the introduction of machine learning models primarily in critical areas is the lack of explainability. In this work, a practicable approach of gaining explainability of deep artificial neural networks (NN) using an ...
Huber, Marco F. +2 more
core +1 more source
Advanced Engineering Materials, EarlyView.A multimaterial approach is introduced to improve upon auxetic structures by combining two different polymers into the same reentrant honeycomb structure via additive manufacturing. The deformation behavior as well as the resulting Poisson's ratio are thereby improved significantly.
Alexander Engel +2 more
wiley +1 more source
Power System Parameters Forecasting Using Hilbert-Huang Transform and Machine Learning [PDF]
, 2014 A novel hybrid data-driven approach is developed for forecasting power system parameters with the goal of increasing the efficiency of short-term forecasting studies for non-stationary time-series. The proposed approach is based on mode decomposition and
Kurbatsky, Victor +5 more
core +2 more sources
Advanced Engineering Materials, EarlyView.This review explores wafer bonding technologies, covering wafer preparation, activation methods, and bonding mechanisms. It compares direct and indirect bonding, highlights recent advancements and future trends, and examines applications in 3D integration and packaging.
Abdul Ahad Khan +5 more
wiley +1 more source
MOOC Dropout Prediction Using a Hybrid Algorithm Based on Decision Tree and Extreme Learning Machine
Mathematical Problems in Engineering, 2019 Massive Open Online Courses (MOOCs) have boomed in recent years because learners can arrange learning at their own pace. High dropout rate is a universal but unsolved problem in MOOCs. Dropout prediction has received much attention recently.
J. Chen +5 more
semanticscholar +1 more source
On Learning Decision Trees with Large Output Domains [PDF]
Algorithmica, 1998 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Nader H. Bshouty +2 more
openaire +2 more sources
Advanced Engineering Materials, EarlyView.The utilization of direct energy deposition (DED)‐arc additive manufacturing processes in industrial applications is increasing, and these processes have the potential for multi‐material applications. This work provides a overview of the state of research in DED‐arc made functional graded structures, to establish a link to potential industrial ...
Kai Treutler, Volker Wesling
wiley +1 more source
Artificial intelligence algorithms for predicting post-operative ileus after laparoscopic surgery
HeliyonObjective: By constructing a predictive model using machine learning and deep learning technologies, we aim to understand the risk factors for postoperative intestinal obstruction in laparoscopic colorectal cancer patients, and establish an effective ...
Cheng-Mao Zhou +4 more
doaj +1 more source
Handwritten digits recognition with decision tree classification: a machine learning approach
International Journal of Electrical and Computer Engineering (IJECE), 2019 Handwritten digits recognition is an area of machine learning, in which a machine is trained to identify handwritten digits. One method of achieving this is with decision tree classification model.
Tsehay Admassu Assegie, Pramod S. Nair
semanticscholar +1 more source