# shn

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 Nov20 accepted Line of best fit (Linear regression) over vertical line Oct21 accepted Euclidean distance is usually not good for sparse data? Oct5 awarded Notable Question Sep29 asked Learning with noisy labels for classification Aug29 awarded Popular Question Aug29 awarded Popular Question Jun17 awarded Popular Question Jun8 asked Probability distribution of distances to micro-cluster centers using particle filtering May13 asked Getting the degree of overlap between each pair of classes Apr30 comment Line of best fit (Linear regression) over vertical line If Y varies and X varies by very slightly, I'll also get the same problem to estimate that line or not ? Apr30 comment Line of best fit (Linear regression) over vertical line Or (1) is it possible to just flip/swap X and Y when the coefficient of correlation is close to 1 ?! (2) It will be close to 1 if we have the case that I shown on the image that I posted ? Apr30 comment Line of best fit (Linear regression) over vertical line Ok, I'll test using the coefficient of correlation and add some random noise to x (is this want you call jitter?) is the correlation is close to 1. I'm using python, sklearn, and the format of the data is just a matrix. Apr30 comment Line of best fit (Linear regression) over vertical line I can not catch this special case where Y do not depends on X, can I ? How ? Or should I always add some noise to my X values ?! Apr30 comment Line of best fit (Linear regression) over vertical line Basically, I want to draw a line which is as close as possible to all points (as a linear regression will do in case where Y depends on X) even if there is no correlation between Y and X values ... I want a method which I can apply whatever is the correlation of Y and X (even there is or there no correlation between them) ! How to do that ? Apr30 comment Line of best fit (Linear regression) over vertical line And this is not for prediction, it is for a pattern recognition problem, where my points are some pixels defined by their coordinates x,y on the image ... Apr30 comment Line of best fit (Linear regression) over vertical line This is just a special case, we can have data where X do not change and Y values changes, or not. I want to draw a line of best fit in all cases ... whatever is my data. Apr30 comment Line of best fit (Linear regression) over vertical line If I give you some data points where X do not change while Y values change. Y do not depends on X. I'm not looking to learn a predictive model. However, I can draw a vertical line which passes over all that points. This is just what I want ! Apr30 comment Line of best fit (Linear regression) over vertical line So to be more clear: My objective is not to predict some y values based on new values of x, my objective is rather just to get a line which passes as close as possible to all points that we have (even if Y are independent of X ...). Apr30 revised Line of best fit (Linear regression) over vertical line added 614 characters in body Apr30 comment Line of best fit (Linear regression) over vertical line I think that I was not very clear in my question. I want to fit the data whatever is the correlation between X and Y (this is not regression), the objective is not to predict some y values based on new values of x, my objective is rather to get a line which passes as close as possible to all points that we have.