Feature selection techniques in the context of big data: taxonomy and analysis
Abstract Recent advancements in Information Technology (IT) have engendered the rapid
production of big data, as enormous volumes of data with high dimensional features grow …
production of big data, as enormous volumes of data with high dimensional features grow …
[PDF][PDF] Literature review on feature selection methods for high-dimensional data
DAA Gnana, SAA Balamurugan… - International Journal of …, 2016 - researchgate.net
Feature selection plays a significant role in improving the performance of the machine
learning algorithms in terms of reducing the time to build the learning model and increasing …
learning algorithms in terms of reducing the time to build the learning model and increasing …
Breast cancer detection in thermograms using a hybrid of GA and GWO based deep feature selection method
Breast cancer is one of the most common reasons for the premature death of women
worldwide. However, early detection and diagnosis of the same can save many lives …
worldwide. However, early detection and diagnosis of the same can save many lives …
Mayfly in harmony: A new hybrid meta-heuristic feature selection algorithm
T Bhattacharyya, B Chatterjee, PK Singh… - IEEE …, 2020 - ieeexplore.ieee.org
Feature selection is a process to reduce the dimension of a dataset by removing redundant
features, and to use the optimal subset of features for machine learning or data mining …
features, and to use the optimal subset of features for machine learning or data mining …
Genetic algorithms in feature and instance selection
CF Tsai, W Eberle, CY Chu - Knowledge-Based Systems, 2013 - Elsevier
Feature selection and instance selection are two important data preprocessing steps in data
mining, where the former is aimed at removing some irrelevant and/or redundant features …
mining, where the former is aimed at removing some irrelevant and/or redundant features …
Handwritten Bangla Character Recognition Using the State‐of‐the‐Art Deep Convolutional Neural Networks
In spite of advances in object recognition technology, handwritten Bangla character
recognition (HBCR) remains largely unsolved due to the presence of many ambiguous …
recognition (HBCR) remains largely unsolved due to the presence of many ambiguous …
An ensemble of deep transfer learning models for handwritten music symbol recognition
In ancient times, there was no system to record or document music. A basic notation system
to write European music was formulated around 14th century in the Baroque period which …
to write European music was formulated around 14th century in the Baroque period which …
Handwritten bangla digit recognition using deep learning
In spite of the advances in pattern recognition technology, Handwritten Bangla Character
Recognition (HBCR)(such as alpha-numeric and special characters) remains largely …
Recognition (HBCR)(such as alpha-numeric and special characters) remains largely …
A multi-scale deep quad tree based feature extraction method for the recognition of isolated handwritten characters of popular indic scripts
Recognition of handwritten characters is a challenging task. Variations in writing styles from
one person to another, as well as for a single individual from time to time, make this task …
one person to another, as well as for a single individual from time to time, make this task …
Two decades of bengali handwritten digit recognition: A survey
Handwritten Digit Recognition (HDR) is one of the most challenging tasks in the domain of
Optical Character Recognition (OCR). Irrespective of language, there are some inherent …
Optical Character Recognition (OCR). Irrespective of language, there are some inherent …