Linked Questions

I was wondering if it is necessary to mean center and set std to 1 to the both my xs and ys in linear regression or doing that to just xs is fine enough. Lets say I use a different model, say neural ...

In some literature, I have read that a regression with multiple explanatory variables, if in different units, needed to be standardized. (Standardizing consists in subtracting the mean and dividing ...

What are the best (recommended) pre-processing steps before performing k-means?

I am working with many algorithms: RandomForest, DecisionTrees, NaiveBayes, SVM (kernel=linear and rbf), KNN, LDA and XGBoost. All of them were pretty fast except for SVM. That is when I got to know ...

Under what circumstances should the data be normalized/standardized when building a regression model. When i asked this question to a stats major, he gave me an ambiguous answer "depends on the data". ...

I have 2 simple questions about linear regression: When is it advised to standardize the explanatory variables? Once estimation is carried out with standardized values, how can one predict with new ...

I was reading the following justification (from cs229 course notes) on why we divide the raw data by its standard deviate: even though I understand what the explanation is saying, it is not clear to ...

I'm curious how an online dating systems might use survey data to determine matches. Suppose they have outcome data from past matches (e.g., 1 = happily married, 0 = no 2nd date). Next, let's ...

When the dependent variable is standardized, how does one interpret the regression coefficients of continuous or categorical independent variables? For instance, if we have $K$ groups in the data and ...

Related reading: When conducting multiple regression, when should you center your predictor variables & when should you standardize them? When and how to use standardized explanatory variables in ...

I am planning to predict a binomial variable (1/0, a used point by an animal or point available to an animal in its range) using several continuous, distance-based predictor variables (distance to ...

I'm working in R, using glm.nb (of the MASS package) to model count data with a negative binomial regression model. I'd like to compare the relative importance of each of my predictor variables ...

I've got a question concerning leave-one-subject-out cross-validation of a classifier and correct outlier handling in this case. Let's suppose I've got 5 subjects. Within each subject the features ...

The classifier is KNN or RBF-SVM. After doing dimension reduction (e.g., PCA, LDA or KPCA, KLDA), does it need to do normalization before classification? In LIBSVM ...

I'm reading an article about Direct Linear Transformation which processes data using SVD, and the data set is standardized so that it has zero mean and unit standard deviation (n.b., some people call ...