Driving behaviour analysis has drawn much attention in recent years due to the dramatic increase in the number of traffic accidents and casualties, and based on many studies, there is a relationship between the driving environment or behaviour and the driver's state. To the best of o...
we introduce a new approach that uses model-internal information from compound activity predictions to uncover relationships between target proteins. On the basis of a large-scale analysis generating and comparing machine learning models for
Other statistical analysis includedregression analysis(n= 8), discriminant analysis (n = 1), partial least squares regression analysis (n = 1),structural equation modelling(SEM) (n = 1), covariance-based SEM (CB-SEM) (n = 1), multi-class classification usingmachine learning algorithms(n = ...
Correlation-Based Comparative Machine Learning Analysis for the Classification of Metastatic Breast Cancer Using Blood Profile As one of the most serious types of cyber attack, Advanced Persistent Threats (APT) have caused major concerns on a global scale. APT refers to a persisten... Botlagunta,...
A faster method is to use machine learning based correlation analysis in order to group related metrics together. In this way, when a metric becomes anomalous, all the related events and metrics that are also anomalous are grouped together in a single incident. This helps to reduce data process...
Multi-view learning (MVL) is a strategy for fusing data from different sources or subsets. Canonical correlation analysis (CCA) is very important in MVL, whose main idea is to map data from different views onto a common space with the maximum correlation. The traditional CCA can only be used...
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pythondatacorrelationanalysismodelingplotroc UpdatedOct 3, 2024 Python emoen/Machine-Learning-for-Asset-Managers Star496 Implementation of code snippets, exercises and application to live data from Machine Learning for Asset Managers (Elements in Quantitative Finance) written by Prof. Marcos López de Pr...
We introduce Deep Canonical Correlation Analysis (DCCA), a method to learn complex nonlinear transformations of two views of data such that the resulting representations are highly linearly correlated. Parameters of both transformations are jointly learned to maximize the (regularized) total correlation. ...
Machine Learning Essentials: Practical Guide in R by A. Kassambara (Datanovia) R Graphics Essentials for Great Data Visualization by A. Kassambara (Datanovia) GGPlot2 Essentials for Great Data Visualization in R by A. Kassambara (Datanovia) Network Analysis and Visualization in R by A. Kass...