Top "Regression" questions

Regression analysis is a collection of statistical techniques for modeling and predicting one or multiple variables based on other data.

Difference between cross_val_score and cross_val_predict

I want to evaluate a regression model build with scikitlearn using cross-validation and getting confused, which of the two functions …

python machine-learning scikit-learn regression cross-validation
Multivariate (polynomial) best fit curve in python?

How do you calculate a best fit line in python, and then plot it on a scatterplot in matplotlib? I …

python matplotlib machine-learning regression scatter-plot
Linear regression line in MATLAB scatter plot

I am trying to get the residuals for the scatter plot of two variables. I could get the least squares …

matlab regression least-squares
Keras - How to perform a prediction using KerasRegressor?

I am new to machine learning, and I am trying to handle Keras to perform regression tasks. I have implemented …

machine-learning scikit-learn neural-network regression keras
Getting glmnet coefficients at 'best' lambda

I am using following code with glmnet: > library(glmnet) > fit = glmnet(as.matrix(mtcars[-1]), mtcars[,1]) > plot(…

r regression glmnet coefficients
tensorflow deep neural network for regression always predict same results in one batch

I use a tensorflow to implement a simple multi-layer perceptron for regression. The code is modified from standard mnist classifier, …

python neural-network regression tensorflow
Fixed effect in Pandas or Statsmodels

Is there an existing function to estimate fixed effect (one-way or two-way) from Pandas or Statsmodels. There used to be …

python pandas regression statsmodels
R nls singular gradient

I've tried searching the other threads on this topic but none of the fixes are working for me. I have …

r regression nls
Time series prediction using R

I have the following R code library(forecast) value <- c(1.2, 1.7, 1.6, 1.2, 1.6, 1.3, 1.5, 1.9, 5.4, 4.2, 5.5, 6, 5.6, 6.2, 6.8, 7.1, 7.1, 5.8, 0, 5.2, 4.6, 3.6, 3, 3.8, 3.1, 3.4, 2, 3.1, 3.2, 1.6, 0.6, 3.3, 4.9, 6.5, 5.3, 3.5, 5.3, 7.2, 7.4, 7.3, 7.2, 4, 6.1, 4.3, 4, 2.4, 0.4, 2.4) sensor<-ts(value,frequency=24) fit <- …

r time-series regression linear-regression forecasting
How to add interaction term in Python sklearn

If I have independent variables [x1, x2, x3] If I fit linear regression in sklearn it will give me something …

python scikit-learn regression linear-regression