Dear:
Within the statistical process, there is a model (Mahalanobis Distance) that is used to support the regression. When is the ratio good on this scale? And why most Arab studies do not rely on it and do not refer to it. But most foreign studies rely on it to support the results of linear and multiple regression. Is it possible to clarify it? What is the best reliable percentage, as high and low values appear in spss?
ههههههه اعرف الاجابة بس خلي انشوف اصدقاء منو يعرف فلم مهالانوبيس
ومستقبلا انت تشتغل العملي واني اشتغل النظري لان طلعت فد شي بالتحليل بالمناسبة لازم عدنا قمر صناعي علمود نشتغل التحليل حول مسافة مهالانوبيس
Mahalanobis distance is an effective multivariate distance metric that measures the distance between a point and a distribution. It is an extremely useful metric having, excellent applications in multivariate anomaly detection, classification on highly imbalanced datasets and one-class classification. This post explains the intuition and the math with practical examples on three machine learning use cases.
https://www.machinelearningplus.com/statistics/mahalanobis-distance/
You might look at the attached paper and recall that discriminant analysis is comparable to logistic regression as well as multivariate OLS, See the link:
https://www.bing.com/search?q=comparing+logistic+regression+and+discriminant+analysis&FORM=AWRE and the two attachments
Best, David Booth
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