InTowards DevbyNivedita BhadraRadar chart - a visualization tool for multivariate dataCompare the effect of different variables in a multivariate analysis4d ago
InAI AdvancesbyKrisztian MagoriChatGPT-4o can run Principal Component Analysis — but I can’t recommend it for other similar…For the last several weeks, during benchmarking the ability of ChatGPT-4o to correctly and reliably run a series of univariate statistical…Nov 238
Muhammad SaleemA Data Scientist’s Perspective: Comparing Logistic Regression and Discriminant AnalysisMultivariate techniques, Logistic and Discriminant analysisNov 711Nov 711
Alhassan AhmedWhy the Gradient Vector Always Points Toward the Direction of the Steepest AscentIf you have taken a multivariable Calculus Course, You have already heard the phrase “The Gradient Vector always points towards the…Nov 92Nov 92
InTowards Data SciencebyErdogan TaskesenOutlier Detection Using Principal Component Analysis and Hotelling’s T2 and SPE/DmodX MethodsThanks to PCA’s sensitivity, it can be used to detect outliers in multivariate datasetsMar 11, 20232Mar 11, 20232
InTowards DevbyNivedita BhadraRadar chart - a visualization tool for multivariate dataCompare the effect of different variables in a multivariate analysis4d ago
InAI AdvancesbyKrisztian MagoriChatGPT-4o can run Principal Component Analysis — but I can’t recommend it for other similar…For the last several weeks, during benchmarking the ability of ChatGPT-4o to correctly and reliably run a series of univariate statistical…Nov 238
Muhammad SaleemA Data Scientist’s Perspective: Comparing Logistic Regression and Discriminant AnalysisMultivariate techniques, Logistic and Discriminant analysisNov 711
Alhassan AhmedWhy the Gradient Vector Always Points Toward the Direction of the Steepest AscentIf you have taken a multivariable Calculus Course, You have already heard the phrase “The Gradient Vector always points towards the…Nov 92
InTowards Data SciencebyErdogan TaskesenOutlier Detection Using Principal Component Analysis and Hotelling’s T2 and SPE/DmodX MethodsThanks to PCA’s sensitivity, it can be used to detect outliers in multivariate datasetsMar 11, 20232
haversteinMahalanobis Distance: An approach for outlier detection in multi-D“Sometimes the most important truths lie on the edges, in the outliers.” — Jonathan IveAug 18
Allan victorAn Intuitive Guide to Principal Component Analysis (PCA) in R: A Step-by-Step Tutorial with…“Don’t give up seeing the exhaustive lines of code. It’s just copy and paste then Run!!”. Stay with me, and I will show you how to generate…Nov 20, 20235
