for issues related to linear regression modelling approach
I am performing a least squares regression as below (univariate). I would like to express the significance of the result …
python numpy linear-regressionI am trying to run a usual linear regression in Python using sk-learn, but I have some categorical data that …
python scikit-learn linear-regression categorical-dataI would like to know how to constrain certain parameters in lm() to have positive coefficients. There are a few …
r regression linear-regression glm lmI'm new to Machine Learning and currently got stuck with this. First I use linear regression to fit the training …
python machine-learning linear-regression polynomialsI am performing lasso regression in R using glmnet package: fit.lasso <- glmnet(x,y) plot(fit.lasso,…
r linear-regression glmnet lasso-regressionI have an example dataset below. train<-data.frame(x1 = c(4,5,6,4,3,5), x2 = c(4,2,4,0,5,4), x3 = c(1,1,1,0,0,1), x4 = c(1,0,1,1,0,0), x5 = c(0,0,0,1,1,1)) …
r regression linear-regression lm mlmI have a very specific requirement for interpolating nonlinear data using a 6th degree polynomial. I've seen numpy/scipy routines (…
python numpy scipy curve-fitting linear-regression> reg.len <- lm(chao1.ave ~ lg.std.len, b.div) # b.div is my data frame imported …
r linear-regression lm predictIn order to combine 3 different estimators of the same variable I need to implement a multiple regression method in Java (…
java regression linear-regression least-squaresReviewing linear regressions via statsmodels OLS fit I see you have to use add_constant to add a constant '1…
python linear-regression statsmodels