Results 31 to 40 of about 3,838 (180)

Multi-Label Opinion Mining Based on Random Forest with SMOTE and ADASYN

Compiler
Multi-label classification is essential to categorize data into multiple labels simultaneously. However, data imbalance poses a challenge, where some labels have much less representation, thus reducing the model performance.
Ricy Ardiansyah, Herman Yuliansyah, Anton Yudhana   +2 more
doaj   +1 more source

A Novel Wireless Network Intrusion Detection Method Based on Adaptive Synthetic Sampling and an Improved Convolutional Neural Network

IEEE Access, 2020
The diversity of network attacks poses severe challenges to intrusion detection systems (IDSs). Traditional attack recognition methods usually adopt mining data associations to identify anomalies, which has the disadvantages of a high false alarm rate ...
Zhiquan Hu, Liejun Wang, Lei Qi, Yongming Li, Wenzhong Yang   +4 more
doaj   +1 more source

Analyzing risk factors and handling imbalanced data for predicting stroke risk using machine learning

IJAIN (International Journal of Advances in Intelligent Informatics)
Stroke is a serious medical condition resulting from disturbances in blood flow to the brain, signaling a chronic health issue that requires an immediate response.
Adiwijaya Adiwijaya, Nur Ghaniaviyanto Ramadhan   +1 more
doaj   +1 more source

Deep Multi-Modal Classification of Intraductal Papillary Mucinous Neoplasms (IPMN) with Canonical Correlation Analysis

, 2018
Pancreatic cancer has the poorest prognosis among all cancer types. Intraductal Papillary Mucinous Neoplasms (IPMNs) are radiographically identifiable precursors to pancreatic cancer; hence, early detection and precise risk assessment of IPMN are vital ...
Bagci, Ulas, Bolan, Candice W., Corral, Juan E., Hussein, Sarfaraz, Kandel, Pujan, Wallace, Michael B.   +5 more
core   +1 more source

Rockburst prediction based on data preprocessing and hyperband‐RNN‐DNN

Deep Underground Science and Engineering, EarlyView.
A data preprocessing workflow is proposed to address challenges in rockburst data analysis. Coupled algorithms preprocess the data set, and hyperband optimization is used to enhance RNN performance. Results show that preprocessing improves accuracy, while dense layers enhance model stability and prediction performance.
Yong Fan, Chenxi Yin, Guangdong Yang, Shengyong Ding, Bin Tian   +4 more
wiley   +1 more source

ENSEMBLE RESAMPLING SUPPORT VECTOR MACHINE, MULTINOMIAL REGRESSION TO MULTICLASS IMBALANCED DATA

Barekeng
Imbalanced data is a commonly encountered issue in classification analysis. This issue gives rise to prediction errors in the classification process, which in turn affects the sensitivity, particularly in the minority class.
Laila Qadrini, Hikmah Hikmah, Elviani Tande, Ignasius Presda, Aulia Atika Maghfirah, Nilawati Nilawati, Handayani Handayani   +6 more
doaj   +1 more source

Malware Detection using Machine Learning and Deep Learning

, 2019
Research shows that over the last decade, malware has been growing exponentially, causing substantial financial losses to various organizations. Different anti-malware companies have been proposing solutions to defend attacks from these malware.
A Nappa, I Santos, MM Masud, R Moskovitch, SK Sahay, Y Ye, Y Ye   +6 more
core   +1 more source

Rhyming in the cold: first evidence of soniferous fishes in the Southern Ocean

Remote Sensing in Ecology and Conservation, EarlyView.
The acoustic ecology of Southern Ocean fishes remains unknown due to a lack of dedicated acoustic research on the fishes of this ocean. Passive acoustic monitoring data were collected at the South African sub‐Antarctic Prince Edward Islands using an underwater acoustic recorder, and towed underwater Ski‐Monkey cameras were deployed to identify fish ...
Fannie W. Shabangu, Grant van der Heever, Charles von der Meden, Hannah Truter, Stephen J. Lamberth, Ofer Gon   +5 more
wiley   +1 more source

Stacking of DT, RF, and Gradient Boosting Algorithms for Classification of Building Damage Due to Earthquakes

Journal of Applied Informatics and Computing
Classification of building damage levels due to earthquakes is an important aspect in disaster mitigation and post-disaster risk assessment. This study aims to improve classification accuracy on imbalanced data using an ensemble stacking method.
Nur Aqliah Ilmi, Nurul Anisa Sri Winarsih   +1 more
doaj   +1 more source

Comparison of Deep Learning and the Classical Machine Learning Algorithm for the Malware Detection

, 2018
Recently, Deep Learning has been showing promising results in various Artificial Intelligence applications like image recognition, natural language processing, language modeling, neural machine translation, etc.
Rathore, Hemant, Sahay, Sanjay K., Sewak, Mohit   +2 more
core   +1 more source