standardized | 易学教程

Can anyone explain me StandardScaler?

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问题 I am unable to understand the page of the StandardScaler in the documentation of sklearn . Can anyone explain this to me in simple terms? 回答1: The idea behind StandardScaler is that it will transform your data such that its distribution will have a mean value 0 and standard deviation of 1. In case of multivariate data, this is done feature-wise (in other words independently for each column of the data). Given the distribution of the data, each value in the dataset will have the mean value

How does this code for standardizing data work?

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问题 I have a provided standardize function for a machine learning course that wasn't well documented and I'm still new to MATLAB so I'm just trying to break down the function. Any explanation of the syntax or the general idea of standardizing would greatly help. We use this function to standardize a set of training data provided in a large matrix. A break down of most of the lines of the code snippet would help me greatly. Thank you so much. function [X, mean_X, std_X] = standardize(varargin)

Standardization/preprocessing for 4-dimensional array

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问题 I'd like to standardize my data to zero mean and std = 1. The shape of my data is 28783x4x24x7, and it can thought of as 28783 images with 4 channels and dimensions 24x7. The channels need to be standardized. How do I standardize while specifying that the 2nd dimension holds the features? 回答1: I found a way to do it. It's perhaps not the most efficient, but it also allows me to use this approach for cross-validation, where I only want to obtain the mean and std from my training data, but

Including standardized coefficients in a stargazer table

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问题 I have a series of linear models and I'd like to report the standardized coefficients for each. However, when I print the models in stargazer, it looks like stargazer automatically prints the significance stars for the standardized coefficients as if they were unstandardized coefficients. You can see how the differences emerge below. Is it statistically wrong to print the significance stars based on the unstandardized values? How is this done in stargazer? Thanks! #load libraries library

python pandas standardize column for regression

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问题 I have the following df: Date Event_Counts Category_A Category_B 20170401 982457 0 1 20170402 982754 1 0 20170402 875786 0 1 I am preparing the data for a regression analysis and want to standardize the column Event_Counts, so that it's on a similar scale like the categories. I use the following code: from sklearn import preprocessing df['scaled_event_counts'] = preprocessing.scale(df['Event_Counts']) While I do get this warning: DataConversionWarning: Data with input dtype int64 was

How to store scaling parameters for later use

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问题 I want to apply the scaling sklearn.preprocessing.scale module that scikit-learn offers for centering a dataset that I will use to train an svm classifier. How can I then store the standardization parameters so that I can also apply them to the data that I want to classify? I know I can use the standarScaler but can I somehow serialize it to a file so that I wont have to fit it to my data every time I want to run the classifier? 回答1: I think that the best way is to pickle it post fit , as

How to store scaling parameters for later use

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I want to apply the scaling sklearn.preprocessing.scale module that scikit-learn offers for centering a dataset that I will use to train an svm classifier. How can I then store the standardization parameters so that I can also apply them to the data that I want to classify? I know I can use the standarScaler but can I somehow serialize it to a file so that I wont have to fit it to my data every time I want to run the classifier? I think that the best way is to pickle it post fit , as this is the most generic option. Perhaps you'll later create a pipeline composed of both a feature extractor

How does this code for standardizing data work?

阅读更多关于 How does this code for standardizing data work?

I have a provided standardize function for a machine learning course that wasn't well documented and I'm still new to MATLAB so I'm just trying to break down the function. Any explanation of the syntax or the general idea of standardizing would greatly help. We use this function to standardize a set of training data provided in a large matrix. A break down of most of the lines of the code snippet would help me greatly. Thank you so much. function [X, mean_X, std_X] = standardize(varargin) switch nargin case 1 mean_X = mean(varargin{1}); std_X = std(varargin{1}); X = varargin{1} - repmat(mean_X