[HTML][HTML] Relief-based feature selection: Introduction and review
Feature selection plays a critical role in biomedical data mining, driven by increasing feature
dimensionality in target problems and growing interest in advanced but computationally …
dimensionality in target problems and growing interest in advanced but computationally …
Ensembles for feature selection: A review and future trends
Ensemble learning is a prolific field in Machine Learning since it is based on the assumption
that combining the output of multiple models is better than using a single model, and it …
that combining the output of multiple models is better than using a single model, and it …
The state of the art and taxonomy of big data analytics: view from new big data framework
Big data has become a significant research area due to the birth of enormous data
generated from various sources like social media, internet of things and multimedia …
generated from various sources like social media, internet of things and multimedia …
Prediction for global African swine fever outbreaks based on a combination of random forest algorithms and meteorological data
R Liang, Y Lu, X Qu, Q Su, C Li, S **
Reliable flash flood susceptibility maps are a vital tool for land planners and emergency
management officials for early flood warning and mitigation. We have developed a new …
management officials for early flood warning and mitigation. We have developed a new …
Scalable feature selection using ReliefF aided by locality‐sensitive hashing
Feature selection algorithms, such as ReliefF, are very important for processing high‐
dimensionality data sets. However, widespread use of popular and effective such algorithms …
dimensionality data sets. However, widespread use of popular and effective such algorithms …
Distributed correlation-based feature selection in spark
Feature selection (FS) is a key preprocessing step in data mining. CFS (Correlation-Based
Feature Selection) is an FS algorithm that has been successfully applied to classification …
Feature Selection) is an FS algorithm that has been successfully applied to classification …
Challenges and future trends for microarray analysis
The current situation in microarray data analysis and prospects for the future are briefly
discussed in this chapter, in which the competition between microarray technologies and …
discussed in this chapter, in which the competition between microarray technologies and …