A comprehensive survey on feature selection in the various fields of machine learning
Abstract In Machine Learning (ML), Feature Selection (FS) plays a crucial part in reducing
data's dimensionality and enhancing any proposed framework's performance. However, in …
data's dimensionality and enhancing any proposed framework's performance. However, in …
Advances in computational intelligence of polymer composite materials: machine learning assisted modeling, analysis and design
The superior multi-functional properties of polymer composites have made them an ideal
choice for aerospace, automobile, marine, civil, and many other technologically demanding …
choice for aerospace, automobile, marine, civil, and many other technologically demanding …
Feature selection in machine learning: A new perspective
J Cai, J Luo, S Wang, S Yang - Neurocomputing, 2018 - Elsevier
High-dimensional data analysis is a challenge for researchers and engineers in the fields of
machine learning and data mining. Feature selection provides an effective way to solve this …
machine learning and data mining. Feature selection provides an effective way to solve this …
[HTML][HTML] Evaluation of feature selection methods for text classification with small datasets using multiple criteria decision-making methods
G Kou, P Yang, Y Peng, F **: A comparison between logistic model tree, logistic regression, naïve bayes tree, artificial neural network, and support vector …
Shallow landslides damage buildings and other infrastructure, disrupt agriculture practices,
and can cause social upheaval and loss of life. As a result, many scientists study the …
and can cause social upheaval and loss of life. As a result, many scientists study the …
The impact of preprocessing on text classification
Preprocessing is one of the key components in a typical text classification framework. This
paper aims to extensively examine the impact of preprocessing on text classification in terms …
paper aims to extensively examine the impact of preprocessing on text classification in terms …
Binary biogeography-based optimization based SVM-RFE for feature selection
Rapid data growth presents many challenges for Machine Learning (ML) tasks as it can
include lots of irrelevant, noisy, and redundant features. Thus, it is vital to select the most …
include lots of irrelevant, noisy, and redundant features. Thus, it is vital to select the most …
The role of text pre-processing in sentiment analysis
It is challenging to understand the latest trends and summarise the state or general opinions
about products due to the big diversity and size of social media data, and this creates the …
about products due to the big diversity and size of social media data, and this creates the …