A review on extreme learning machine
Extreme learning machine (ELM) is a training algorithm for single hidden layer feedforward
neural network (SLFN), which converges much faster than traditional methods and yields …
neural network (SLFN), which converges much faster than traditional methods and yields …
[HTML][HTML] Credit card fraud detection in the era of disruptive technologies: A systematic review
Credit card fraud is becoming a serious and growing problem as a result of the emergence
of innovative technologies and communication methods, such as contactless payment. In …
of innovative technologies and communication methods, such as contactless payment. In …
Artificial intelligence and COVID-19: deep learning approaches for diagnosis and treatment
COVID-19 outbreak has put the whole world in an unprecedented difficult situation bringing
life around the world to a frightening halt and claiming thousands of lives. Due to COVID …
life around the world to a frightening halt and claiming thousands of lives. Due to COVID …
[HTML][HTML] The impact of class imbalance in classification performance metrics based on the binary confusion matrix
A major issue in the classification of class imbalanced datasets involves the determination of
the most suitable performance metrics to be used. In previous work using several examples …
the most suitable performance metrics to be used. In previous work using several examples …
Complex-valued neural networks: A comprehensive survey
Complex-valued neural networks (CVNNs) have shown their excellent efficiency compared
to their real counter-parts in speech enhancement, image and signal processing …
to their real counter-parts in speech enhancement, image and signal processing …
[PDF][PDF] Study of variants of extreme learning machine (ELM) brands and its performance measure on classification algorithm
Recently, the feed-forward neural network is functioning with slow computation time and
increased gain. The weight vector and biases in the neural network can be tuned based on …
increased gain. The weight vector and biases in the neural network can be tuned based on …
Non-iterative and fast deep learning: Multilayer extreme learning machines
In the past decade, deep learning techniques have powered many aspects of our daily life,
and drawn ever-increasing research interests. However, conventional deep learning …
and drawn ever-increasing research interests. However, conventional deep learning …
Trends in extreme learning machines: A review
Extreme learning machine (ELM) has gained increasing interest from various research fields
recently. In this review, we aim to report the current state of the theoretical research and …
recently. In this review, we aim to report the current state of the theoretical research and …
An insight into classification with imbalanced data: Empirical results and current trends on using data intrinsic characteristics
Training classifiers with datasets which suffer of imbalanced class distributions is an
important problem in data mining. This issue occurs when the number of examples …
important problem in data mining. This issue occurs when the number of examples …
A cost-sensitive deep belief network for imbalanced classification
Imbalanced data with a skewed class distribution are common in many real-world
applications. Deep Belief Network (DBN) is a machine learning technique that is effective in …
applications. Deep Belief Network (DBN) is a machine learning technique that is effective in …