Skip to main content

New answers tagged

0 votes

Should I Use Regularization in Univariate Logistic Regression for Diagnostic Methods Comparison?

I assume your goal is to predict Method 2 with Method 1's value. Regularization shrinks the parameter to 0. As you have only one input, the shrinkage is less meaningful. I view the regularization ...
Xiaochuan Lu's user avatar
1 vote
Accepted

Why the contribution of a categorical value in SHAP trained on Catboost differs from observation to observation

There is a difference because the effect of the species ("target") is not independent of the other features: the GBM you have built has nontrivial (and perhaps even very complex) feature ...
Ben Reiniger's user avatar
  • 4,767
0 votes

VIF for Categorical Variable with More Than 2 Categories

I was having the same problem with my dataset. What I found with R is that it can handle un-labelled categorical variable also with GVIF function. It means you can keep the categorical data in a ...
yashodhar pathak's user avatar
0 votes

Can I use simulated data only for testing a Random Forest regression already trained on real data?

This is generally good practice for understanding many machine learning models, and some complex statistical models. It's especially valuable as a way to evaluate how the model extrapolates. In the ...
mkt's user avatar
  • 18.9k
1 vote

Multi Level / Hierarchical Time Series Models in Python

STAN may be an option. It has a Python interface. see: https://mc-stan.org/docs/stan-users-guide/regression.html#hierarchical-regression
user1747134's user avatar
1 vote

Regression analysis with max value

If this is your actual data set, then you do not have enough to fit more than a linear or maybe a quadratic. Then you have the problem of a few points that are identical, and an outlier. If you cannot ...
Peter Flom's user avatar
  • 125k
3 votes
Accepted

Calculating error on a double natural log fit

It is surprising that you call "double log fit" because this is a single log fit : $$y=a\ln(pt)+b\ln(qt)$$ $y=\ln(p^a t^a)+\ln(q^b t^b)=\ln\left((p^a t^a)(q^b t^b) \right)=\ln(p^aq^bt^{a+b})=...
JJacquelin's user avatar
0 votes

How can I calibrate my point-by-point variances for Gaussian process regression?

A skeleton example implementing user21060's answer using tinygp: ...
hobbs's user avatar
  • 289
1 vote

Breusch Pagan test in Python

The Breusch-Pagan test aims to detect heteroscedasticity in a regression model (the presence of non-constant variance in the error terms). The ...
Robert Long's user avatar
  • 64.1k
2 votes
Accepted

Modeling a functional relationship with Constrained Gaussian Process regression

To address the problem of modeling a nonlinear relationship with a response variable $y \in (0,1)$, one viable approach is to use a Gaussian Process (GP) model while transforming the response variable ...
Robert Long's user avatar
  • 64.1k
3 votes

Why RandomForestRegressor.score() return a coefficient of determination?

Wikipedia: the coefficient of determination, denoted $R^2$ or $r^2$ and pronounced "R squared", is the proportion of the variation in the dependent variable that is predictable from the ...
Stephan Kolassa's user avatar

Top 50 recent answers are included