A review of the multi-dimensional application of machine learning to improve the integrated intelligence of laser powder bed fusion
Laser powder bed fusion (LPBF) as one of the most promising additive manufacturing (AM)
technologies, has been widely used to produce metal parts and applied in fields such as …
technologies, has been widely used to produce metal parts and applied in fields such as …
Offensive language detection in social media using ensemble techniques
J Preetham, J Anitha - 2023 International Conference on …, 2023 - ieeexplore.ieee.org
Hate speech and offensive content are deliberate attacks directed at a group or society
based on their characteristics like religion, gender, or race, and pose a threat to society. The …
based on their characteristics like religion, gender, or race, and pose a threat to society. The …
Hybrid feature selection algorithm and ensemble stacking for heart disease prediction
NAM Zaini, MK Awang - International Journal of Advanced …, 2023 - search.proquest.com
In cardiology, as in other medical specialties, early and accurate diagnosis of heart disease
is crucial as it has been the leading cause of death over the past few decades. Early …
is crucial as it has been the leading cause of death over the past few decades. Early …
Multiclass intent classification for chatbot based on machine learning algorithm
In recent years, the use of Chatbots has grown significantly in various industries, including
support systems, education, health care, tourism, entertainment, and banking. Chatbot for …
support systems, education, health care, tourism, entertainment, and banking. Chatbot for …
Enhanced approach of multilabel learning for the Arabic aspect category detection of the hotel reviews
In many fields, like aspect category detection (ACD) in aspect‐based sentiment analysis, it is
necessary to label each instance with more than one label at the same time. This study …
necessary to label each instance with more than one label at the same time. This study …
Comparison of Iris dataset classification with Gaussian naïve Bayes and decision tree algorithms.
Y Dani, MA Ginting - International Journal of Electrical & …, 2024 - search.ebscohost.com
In this study, we apply two classification algorithm methods, namely the Gaussian naïve
Bayes (GNB) and the decision tree (DT) classifiers. The Gaussian naïve Bayes classifier is a …
Bayes (GNB) and the decision tree (DT) classifiers. The Gaussian naïve Bayes classifier is a …
[PDF][PDF] An Effective Random Forest Approach for Mining Graded Multi-Label Data.
The graded multi-label classification (GMLC) is an extension of multi-label classification.
Whilst a multilabel classifier is limited to predicting the set of relevant labels, a graded multi …
Whilst a multilabel classifier is limited to predicting the set of relevant labels, a graded multi …
Além do aprendizado local e global: particionando o espaço de classes em problemas de classificação multirrótulo
EC Gatto - 2023 - repositorio.ufscar.br
Inducing a model capable of predicting a set of labels for an instance is the objective of multi-
label classification, a supervised predictive machine learning task. Work in the literature has …
label classification, a supervised predictive machine learning task. Work in the literature has …
[PDF][PDF] Towards Stacking Ensemble-Based Fine-Grained Hostile Class Classification (FGHCC) of Hindi Posts
A Sharma, U Ghose - researchgate.net
Lately, there has been a phenomenal surge in Hostile Online Content (HOC). The detection
and classification of HOC on Online Social Platforms (OSPs) are becoming an important …
and classification of HOC on Online Social Platforms (OSPs) are becoming an important …
[PDF][PDF] THE IMPACT OF SMART TECHNOLOGIES IN E-LEARNING ENVIRONMENT FOR THE PREPARATION OF NEW GENERATION SPECIALISTS
M FIQIYAH, EMEALI HASSAN, S MEI… - jilindaxuexuebao.org
The rapid advancement of smart technologies has revolutionized the field of education,
particularly in the realm of e-learning. This research paper delves into the profound …
particularly in the realm of e-learning. This research paper delves into the profound …