17 papers · ranked by Valyu relevance
Davide Chicco, Giuseppe Jurman
Background To evaluate binary classifications and their confusion matrices, scientific researchers can employ several statistical rates, accordingly to the goal of the experiment they are investigating. Despite being a crucial issue in machine learning, no widespread consensus has been reached on a unified elective…
Sung-Cheol Kim, Adith S. Arun, Mehmet Eren Ahsen, Robert Vogel + 1 more
'Gustavo Stolovitzky'] Title: Significance While it would be desirable that the output of binary classification algorithms be the probability that the classification is correct, most algorithms do not provide a method to calculate such a probability. We propose a probabilistic output for binary classifiers based on an…
Yituo Feng, Jungryeol Park, Varun Gupta
Background In today’s digital economy, enterprises are adopting collaboration software to facilitate digital transformation. However, if employees are not satisfied with the collaboration software, it can hinder enterprises from achieving the expected benefits. Although existing literature has contributed to user…
Minh Long Hoang, Guido Matrella, Paolo Ciampolini, Georg Fischer
This work aims to compare the performance of Machine Learning (ML) and Deep Learning (DL) algorithms in detecting users’ heartbeats on a smart bed. Targeting non-intrusive, continuous heart monitoring during sleep time, the smart bed is equipped with a 3D solid-state accelerometer. Acceleration signals are processed…
Nazhir Amaya-Tejera, Margarita Gamarra, Jorge I. Vélez, Eduardo Zurek
Support Vector Machines (SVMs) are a type of supervised machine learning algorithm widely used for classification tasks. In contrast to traditional methods that split the data into separate training and testing sets, here we propose an innovative approach where subsets of the original data are randomly selected to…
Adi L Tarca, Vincent J Carey, Xue-wen Chen, Roberto Romero + 2 more
Quadratic and linear discriminants. A standard classification approach, applicable when the features are continuous variables (e.g., gene expression data), assumes that for each class c, x follows a multivariate normal distribution N(mc,Σc) having the mean mc and covariance matrix Σc. The covariance matrix Σ is square…
Mert Bal, M. Fatih Amasyali, Hayri Sever, Guven Kose + 1 more
The importance of the decision support systems is increasingly supporting the decision making process in cases of uncertainty and the lack of information and they are widely used in various fields like engineering, finance, medicine, and so forth, Medical decision support systems help the healthcare personnel to select…
Nureni Ayofe Azeez, Sanjay Misra, Davidson Onyinye Ogaraku, Ademola Philip Abidoye + 2 more
The pervasive spread of fake news in online social media has emerged as a critical threat to societal integrity and democratic processes. To address this pressing issue, this research harnesses the power of supervised AI algorithms aimed at classifying fake news with selected algorithms. Algorithms such as Passive…
Sebastian Scheurer, Salvatore Tedesco, Kenneth N. Brown, Brendan O’Flynn
'Brendan O’Flynn'] Human activity recognition (HAR) has become an increasingly popular application of machine learning across a range of domains. Typically the HAR task that a machine learning algorithm is trained for requires separating multiple activities such as walking, running, sitting, and falling from each…
Osvaldo Velazquez-Gonzalez, Antonio Alarcón-Paredes, Cornelio Yañez-Marquez
Classification is a central task in machine learning, underpinning applications in domains such as finance, medicine, engineering, information technology, and biology. However, machine learning pattern classification can become a complex or even inexplicable task for current robust models due to the complexity of…
Vu Ngoc Thanh Sang, Shiro Yano, Toshiyuki Kondo
Many motion sensor-based applications have been developed in recent years because they provide useful information about daily activities and current health status of users. However, most of these applications require knowledge of sensor positions. Therefore, this research focused on the problem of detecting sensor…
Quang Hung Do, Jeng-Fung Chen
Classifying the student academic performance with high accuracy facilitates admission decisions and enhances educational services at educational institutions. The purpose of this paper is to present a neuro-fuzzy approach for classifying students into different groups. The neuro-fuzzy classifier used previous exam…
Hooman H. Rashidi, Samer Albahra, Scott Robertson, Nam K. Tran + 1 more
'Bo Hu'] One of the core elements of Machine Learning (ML) is statistics and its embedded foundational rules and without its appropriate integration, ML as we know would not exist. Various aspects of ML platforms are based on statistical rules and most notably the end results of the ML model performance cannot be…
Sashikala Mishra, Kailash Shaw, Debahuti Mishra, Shruti Patil + 3 more
Healthcare AI systems exclusively employ classification models for disease detection. However, with the recent research advances into this arena, it has been observed that single classification models have achieved limited accuracy in some cases. Employing fusion of multiple classifiers outputs into a single…
Elias Abou Zeid, Alborz Rezazadeh Sereshkeh, Benjamin Schultz, Tom Chau
'Tom Chau'] In recent years, the readiness potential (RP), a type of pre-movement neural activity, has been investigated for asynchronous electroencephalogram (EEG)-based brain-computer interfaces (BCIs). Since the RP is attenuated for involuntary movements, a BCI driven by RP alone could facilitate intentional control…
Alfredo Benso, Stefano Di Carlo, Gianfranco Politano, Alessandro Savino + 1 more
'Alessandro Savino' 'Hafeez Hafeezurrehman'] Background The collection of gene expression profiles from DNA microarrays and their analysis with pattern recognition algorithms is a powerful technology applied to several biological problems. Common pattern recognition systems classify samples assigning them to a set of…
Antonio García-Domínguez, Carlos E. Galván-Tejada, Rafael Magallanes-Quintanar, Hamurabi Gamboa-Rosales + 3 more
'Rafael Magallanes-Quintanar' 'Hamurabi Gamboa-Rosales' 'Irma González Curiel' 'Jesús Peralta-Romero' 'Miguel Cruz'] The development of medical diagnostic models to support healthcare professionals has witnessed remarkable growth in recent years. Among the prevalent health conditions affecting the global population…