normalize

问题 I am using Anaconda with a Tensorflow neural network. Most of my data is stored with pandas . I am attempting to predict cryptocurrency markets. I am aware that this lots of people are probably doing this and it is most likely not going to be very effective, I'm mostly doing it to familiarize myself with Tensorflow and Anaconda tools. I am fairly new to this, so if I am doing something wrong or suboptimally please let me know. Here is how I aquire and handle the data: Download datasets from

问题 I am using Anaconda with a Tensorflow neural network. Most of my data is stored with pandas . I am attempting to predict cryptocurrency markets. I am aware that this lots of people are probably doing this and it is most likely not going to be very effective, I'm mostly doing it to familiarize myself with Tensorflow and Anaconda tools. I am fairly new to this, so if I am doing something wrong or suboptimally please let me know. Here is how I aquire and handle the data: Download datasets from

问题 How to find the values to pass to the transforms.Normalize function in PyTorch? Also, where in my code, should I exactly do the transforms.Normalize? Since normalizing the dataset is a pretty well-known task, I was hoping there should be some sort of script for doing that automatically. At least I couldn't find it in PyTorch forum. transformed_dataset = MothLandmarksDataset(csv_file='moth_gt.csv', root_dir='.', transform=transforms.Compose([ Rescale(256), RandomCrop(224), transforms.Normalize

问题 If we have concrete range of max..min value it is quite easy to normalize it to 0..1 float values, but if we don't have concrete limits? Is it possible to build universal function to have output between 0 and 1? In my mind I think it is impossible but I am not math expert. I'm searching for implementation on JavaScript or PHP, but any code on C/C++/Python/Delphi is OK to provide examples ( if there are some ) 回答1: There are many ways to do this. I'll leave out mapping -inf and +inf , which

问题 If we have concrete range of max..min value it is quite easy to normalize it to 0..1 float values, but if we don't have concrete limits? Is it possible to build universal function to have output between 0 and 1? In my mind I think it is impossible but I am not math expert. I'm searching for implementation on JavaScript or PHP, but any code on C/C++/Python/Delphi is OK to provide examples ( if there are some ) 回答1: There are many ways to do this. I'll leave out mapping -inf and +inf , which

问题 If we have concrete range of max..min value it is quite easy to normalize it to 0..1 float values, but if we don't have concrete limits? Is it possible to build universal function to have output between 0 and 1? In my mind I think it is impossible but I am not math expert. I'm searching for implementation on JavaScript or PHP, but any code on C/C++/Python/Delphi is OK to provide examples ( if there are some ) 回答1: There are many ways to do this. I'll leave out mapping -inf and +inf , which

问题 If we have concrete range of max..min value it is quite easy to normalize it to 0..1 float values, but if we don't have concrete limits? Is it possible to build universal function to have output between 0 and 1? In my mind I think it is impossible but I am not math expert. I'm searching for implementation on JavaScript or PHP, but any code on C/C++/Python/Delphi is OK to provide examples ( if there are some ) 回答1: There are many ways to do this. I'll leave out mapping -inf and +inf , which

来源： https://stackoverflow.com/questions/37341150/error-in-normalize-path-r-shiny

来源： https://stackoverflow.com/questions/52345236/sklearn-preprocessing-typeerror-no-matching-signature-found

问题 I'm currently trying to normalize data with VBA in Excel. Therefore, my workbook imports several csv files and wrote them in different worksheets all of them are built like this. First row: Header First column: x-Axis (for plotting) Second column to nth column: y-values Now I want to normalize all columns from 2 to n (dividing by maximum value of each column). Here is the function I'm using so far: Sub NormalizeData(dataName) cs = Worksheets(dataName).UsedRange.SpecialCells(xlCellTypeLastCell