Is Logistic Regression a classification or prediction model?
Jun 30, 2023 · In this forum, there are opposite opinions(1), (2) on the uses of logistic regression. Ones say, it is a classification model and others say it is a prediction model. Therefore, the …
Computing the variance explained by a predictor variable in …
Sep 20, 2023 · 3 I'm keen to know how to compute the variance explained by a particular predictor variable in the model (say component specific R squared). I went through Calculate …
Walk through `rms::calibrate` for logistic regression
Jan 26, 2022 · The calibrate function in the rms R package allows us to compare the probability values predicted by a logistic regression model to the true probability values. This is easy …
Is standardization needed before fitting logistic regression?
Standardization isn't required for logistic regression. The main goal of standardizing features is to help convergence of the technique used for optimization. For example, if you use Newton …
regression - McFadden's Pseudo-$R^2$ Interpretation - Cross …
Apr 27, 2020 · I have a binary logistic regression model with a McFadden's pseudo R-squared of 0.192 with a dependent variable called payment (1 = payment and 0 = no payment). What is …
r - Difference between logit and probit models - Cross Validated
Mar 27, 2015 · What is the difference between Logit and Probit model? I'm more interested here in knowing when to use logistic regression, and when to use Probit. If there is any literature …
What do the residuals in a logistic regression mean?
In my book Regression Modeling Strategies I downplay the use of residuals in logistic regression because (1) logistic regression makes no distributional assumptions and (2) there are more …
Why is logistic regression a linear model? - Cross Validated
Mar 3, 2014 · I want to know why logistic regression is called a linear model. It uses a sigmoid function, which is not linear. So why is logistic regression a linear model?
Calculating confidence intervals for a logistic regression
Jul 2, 2018 · I'm using a binomial logistic regression to identify if exposure to has_x or has_y impacts the likelihood that a user will click on something. My model is the following: fit = glm …
r - When to remove insignificant variables? - Cross Validated
Jun 18, 2019 · Typically, when you use logistic regression in a business setting, both inferential information about the variables used along with a good prediction are what stakeholders are …