scholarly journals Risk Prediction with Regression in Global Software Development using Machine Learning Approach: A Comparison of Linear and Decision Tree Regression

2021 ◽  
Vol 17 (2) ◽  
pp. 67-89
Author(s):  
Asim Iftikhar ◽  
Shahrulniza Musa ◽  
Muhammad Alam ◽  
Rizwan Ahmed ◽  
Tariq Rahim Soomro ◽  
...  
Keyword(s):  
Machine Learning ◽  
Decision Tree ◽  
Software Development ◽  
Risk Prediction ◽  
Global Software Development ◽  
Learning Approach ◽  
Machine Learning Approach

scholarly journals Application of FURIA for Finding the Faults in a Hydraulic Brake System Using a Vibration Analysis through a Machine Learning Approach

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Alamelu Manghai T. M ◽  
Jegadeeshwaran R
Keyword(s):  
Machine Learning ◽  
Fault Diagnosis ◽  
Decision Tree ◽  
Continuous Monitoring ◽  
Selection Process ◽  
Brake System ◽  
Learning Approach ◽  
Vibration Signals ◽  
Hydraulic Brake ◽  
Machine Learning Approach

Vibration-based continuous monitoring system for fault diagnosis of automobile hydraulic brake system is presented in this study. This study uses a machine learning approach for the fault diagnosis study. A hydraulic brake system test rig was fabricated. The vibration signals were acquired from the brake system under different simulated fault conditions using a piezoelectric transducer. The histogram features were extracted from the acquired vibration signals. The feature selection process was carried out using a decision tree. The selected features were classified using fuzzy unordered rule induction algorithm ( FURIA ) and Repeated Incremental Pruning to Produce Error Reduction ( RIPPER ) algorithm. The classification results of both algorithms for fault diagnosis of a hydraulic brake system were presented. Compared to RIPPER and J48 decision tree, the FURIA performs better and produced 98.73 % as the classification accuracy.

A machine-learning approach to cardiovascular risk prediction in psoriatic arthritis

Rheumatology ◽  
2020 ◽  
Vol 59 (7) ◽  
pp. 1767-1769
Author(s):  
Luca Navarini ◽  
Michela Sperti ◽  
Damiano Currado ◽  
Luisa Costa ◽  
Marco A Deriu ◽  
...  
Keyword(s):  
Machine Learning ◽  
Cardiovascular Risk ◽  
Psoriatic Arthritis ◽  
Risk Prediction ◽  
Learning Approach ◽  
Cardiovascular Risk Prediction ◽  
Machine Learning Approach

Machine learning approach for multi-perspective volcanic eruption recognition using thermal infrared images

2020 ◽  
Author(s):  
Claudia Corradino ◽  
Gaetana Ganci ◽  
Giuseppe Bilotta ◽  
Annalisa Cappello ◽  
Ciro Del Negro
Keyword(s):  
Machine Learning ◽  
Decision Tree ◽  
Real Time ◽  
Mount Etna ◽  
Learning Approach ◽  
Bag Of Words ◽  
Infrared Images ◽  
Machine Learning Approach ◽  
Thermal Infrared Images ◽  
Thermal Cameras

<p>Detect, locate and characterize eruptions in real-time is fundamental to monitor volcanic activity. Here we present an automatic system able to discover and identify the main types of eruptive activities by exploiting infrared images acquired by the thermal cameras installed around Mount Etna volcano. The system, which employs the machine learning approach, is based on a decision tree tool and a bag of words-based classifier. The decision tree provides information on the visibility level of the monitored area, while the bag of words-based classifiers detects the onset of the eruptive activity and recognize the eruption type among either explosion and/or lava flow or plume. Thus, applied to each image of all thermal cameras over Etna in real-time, the proposed system provides two outputs, namely the visibility level and the recognized activity status. By merging the outcomes coming from each thermal camera, the monitored phenomena can be fully described from different perspectives getting deeper information in real-time and in an automatic way.   </p>

scholarly journals A Naive Bayes machine learning approach to risk prediction using censored, time-to-event data

2015 ◽  
Vol 34 (21) ◽  
pp. 2941-2957 ◽  
Author(s):  
Julian Wolfson ◽  
Sunayan Bandyopadhyay ◽  
Mohamed Elidrisi ◽  
Gabriela Vazquez-Benitez ◽  
David M. Vock ◽  
...  
Keyword(s):  
Machine Learning ◽  
Risk Prediction ◽  
Naive Bayes ◽  
Naïve Bayes ◽  
Learning Approach ◽  
Event Data ◽  
Time To Event ◽  
Time To Event Data ◽  
Machine Learning Approach
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