Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
[HTML][HTML] Feature selection and importance of predictors of non-communicable diseases medication adherence from machine learning research perspectives
Medication nonadherence is a significant public health concern that leads to ineffective
treatment, which in turn engenders complications such as increased morbidity risks …
treatment, which in turn engenders complications such as increased morbidity risks …
Cyberbullying detection: Utilizing social media features
Cyberbullying has become a major problem around the world with the increasing usage of
social networks. In this direction, many studies are conducted to detect cyberbullying content …
social networks. In this direction, many studies are conducted to detect cyberbullying content …
Mini-batch normalized mutual information: A hybrid feature selection method
Feature Selection has been a significant preprocessing procedure for classification in the
area of Supervised Machine Learning. It is mostly applied when the attribute set is very …
area of Supervised Machine Learning. It is mostly applied when the attribute set is very …
Deep learning approach to detect cyberbullying on twitter
In recent years, especially children and adolescents have shown increased interest in social
media, making them a potential risk group for cyberbullying. Cyberbullying posts spread …
media, making them a potential risk group for cyberbullying. Cyberbullying posts spread …
Composition of Feature Selection for Time-Series Prediction with Deep Learning
The concept of predictions has gained much attention over the last few years. Research on
prediction based on experience is error-prone. Usually, a lot of data has been available with …
prediction based on experience is error-prone. Usually, a lot of data has been available with …
[HTML][HTML] Hybrid artificial intelligence HFS-RF-PSO model for construction labor productivity prediction and optimization
This paper presents a novel approach, using hybrid feature selection (HFS), machine
learning (ML), and particle swarm optimization (PSO) to predict and optimize construction …
learning (ML), and particle swarm optimization (PSO) to predict and optimize construction …
[HTML][HTML] JoMIC: A joint MI-based filter feature selection method
Feature selection (FS) is a common preprocessing step of machine learning that selects
informative subset of features which fuels a model to perform better during prediction or …
informative subset of features which fuels a model to perform better during prediction or …
Feature selection based on a hybrid simplified particle swarm optimization algorithm with maximum separation and minimum redundancy
L Sun, Y Yang, Y Liu, T Ning - International Journal of Machine Learning …, 2023 - Springer
Feature selection is an important technique of data processing in the field of machine
learning and data mining. Its goal is to select the feature subset with the maximum …
learning and data mining. Its goal is to select the feature subset with the maximum …
Feature selection in high-dimensional data
Today, with the increase of data dimensions, many challenges are faced in many contexts
including machine learning, informatics, and medicine. However, reducing data dimension …
including machine learning, informatics, and medicine. However, reducing data dimension …
[HTML][HTML] Determining the capability of the tree-based pipeline optimization tool (tpot) in map** parthenium weed using multi-date sentinel-2 image data
The Tree-based Pipeline Optimization Tool (TPOT) is a state-of-the-art automated machine
learning (AutoML) approach that automatically generates and optimizes tree-based …
learning (AutoML) approach that automatically generates and optimizes tree-based …