Results 21 to 30 of about 2,759,833 (308)

Feature Selection Embedded Robust K-Means

IEEE Access, 2020
Clustering is one of the most important unsupervised learning problems in machine learning. As one of the most widely used clustering algorithms, K-means has been studied extensively.
Qian Zhang, Chong Peng
doaj   +1 more source

Data Attribute Selection with Information Gain to Improve Credit Approval Classification Performance using K-Nearest Neighbor Algorithm

International Journal of Islamic Business and Economics (IJIBEC), 2017
Credit is one of the modern economic behaviors. In practice, credit can be either borrowing a certain amount of money or purchasing goods with a gradual payment process and within an agreed timeframe.
Ivandari Ivandari, Tria Titiani Chasanah, Sattriedi Wahyu Binabar, M. Adib Al Karomi   +3 more
doaj   +1 more source

Dynamic Feature Selection for Clustering High Dimensional Data Streams

IEEE Access, 2019
Change in a data stream can occur at the concept level and at the feature level. Change at the feature level can occur if new, additional features appear in the stream or if the importance and relevance of a feature changes as the stream progresses. This
Conor Fahy, Shengxiang Yang
doaj   +1 more source

Supervised Feature Selection With a Stratified Feature Weighting Method

IEEE Access, 2018
Feature selection has been a powerful tool to handle high-dimensional data. Most of these methods are biased toward the highest rank features which may be highly correlated with each other.
Renjie Chen, Ning Sun, Xiaojun Chen, Min Yang, Qingyao Wu   +4 more
doaj   +1 more source

New Feature Selection Algorithm Based on Feature Stability and Correlation

IEEE Access, 2022
The analysis of a large amount of data with high dimensionality of rows and columns increases the load of machine learning algorithms. Such data are likely to have noise and consequently, obstruct the performance of machine learning algorithms.
Luai Al-Shalabi
doaj   +1 more source

Feature extraction for epileptic seizure detection using machine learning

Current Medicine Research and Practice, 2020
Background: Epilepsy is a common neurological disorder and affects approximately 70 million people worldwide. The traditional approach used by neurologists for the detection of seizure is time consuming.
Renuka Mohan Khati, Rajesh Ingle
doaj   +1 more source

CBFS: high performance feature selection algorithm based on feature clearness. [PDF]

PLoS ONE, 2012
BACKGROUND: The goal of feature selection is to select useful features and simultaneously exclude garbage features from a given dataset for classification purposes.
Minseok Seo, Sejong Oh
doaj   +1 more source

Infinite Latent Feature Selection: A Probabilistic Latent Graph-Based Ranking Approach [PDF]

, 2017
Feature selection is playing an increasingly significant role with respect to many computer vision applications spanning from object recognition to visual object tracking.
Castellani, Umberto, Melzi, Simone, Roffo, Giorgio, Vinciarelli, Alessandro   +3 more
core   +3 more sources

Biological Invasion-Based Feature Selection Algorithm [PDF]

Jisuanji gongcheng
In nature, biological invasions have attracted attention because of their rapid development and significant ecological impacts. The introduction of populations to search for suitable habitats often has inherent logic, and communication between ...
ZHANG Jian, ZHANG Bo
doaj   +1 more source

Structure Preserving Non-negative Feature Self-Representation for Unsupervised Feature Selection

IEEE Access, 2017
Inspired by the importance of self-representation and structure-preserving ability of features, in this paper, we propose a novel unsupervised feature selection algorithm named structure-preserving non-negative feature self-representation (SPNFSR).
Wei Zhou, Chengdong Wu, Yugen Yi, Guoliang Luo   +3 more
doaj   +1 more source