Learning from imbalanced data
H He, EA Garcia - IEEE Transactions on knowledge and data …, 2009 - ieeexplore.ieee.org
With the continuous expansion of data availability in many large-scale, complex, and
networked systems, such as surveillance, security, Internet, and finance, it becomes critical …
networked systems, such as surveillance, security, Internet, and finance, it becomes critical …
[PDF][PDF] Recommendations for acoustic recognizer performance assessment with application to five common automated signal recognition programs
Automated signal recognition software is increasingly used to extract species detection data
from acoustic recordings collected using autonomous recording units (ARUs), but there is …
from acoustic recordings collected using autonomous recording units (ARUs), but there is …
The relationship between Precision-Recall and ROC curves
Receiver Operator Characteristic (ROC) curves are commonly used to present results for
binary decision problems in machine learning. However, when dealing with highly skewed …
binary decision problems in machine learning. However, when dealing with highly skewed …
PRROC: computing and visualizing precision-recall and receiver operating characteristic curves in R
Precision-recall (PR) and receiver operating characteristic (ROC) curves are valuable
measures of classifier performance. Here, we present the R-package PRROC, which allows …
measures of classifier performance. Here, we present the R-package PRROC, which allows …
Advancing the science for active surveillance: rationale and design for the Observational Medical Outcomes Partnership
PE Stang, PB Ryan, JA Racoosin… - Annals of internal …, 2010 - acpjournals.org
The US Food and Drug Administration (FDA) Amendments Act of 2007 mandated that the
FDA develop a system for using automated health care data to identify risks of marketed …
FDA develop a system for using automated health care data to identify risks of marketed …
NATICUSdroid: A malware detection framework for Android using native and custom permissions
The rapid growth of Android apps and its worldwide popularity in the smartphone market has
made it an easy and accessible target for malware. In the past few years, the Android …
made it an easy and accessible target for malware. In the past few years, the Android …
Predictive analytics for customer repurchase: Interdisciplinary integration of buy till you die modeling and machine learning
Predicting customer repurchase propensity/frequency has received broad research interests
from marketing, operations research, statistics, and computer science. In the field of …
from marketing, operations research, statistics, and computer science. In the field of …
Tensor factorization for multi-relational learning
Tensor factorization has emerged as a promising approach for solving relational learning
tasks. Here we review recent results on a particular tensor factorization approach, ie Rescal …
tasks. Here we review recent results on a particular tensor factorization approach, ie Rescal …
Bridging expert knowledge with deep learning techniques for just-in-time defect prediction
Abstract Just-In-Time (JIT) defect prediction aims to automatically predict whether a commit
is defective or not, and has been widely studied in recent years. In general, most studies can …
is defective or not, and has been widely studied in recent years. In general, most studies can …
A literature survey on various aspect of class imbalance problem in data mining
S Goswami, AK Singh - Multimedia Tools and Applications, 2024 - Springer
Data has become much widely available in recent years. Since the past years, Learning
classifiers from unbalanced data is a crucial issue that comes up frequently in classification …
classifiers from unbalanced data is a crucial issue that comes up frequently in classification …