machine learning - Definition of Regressor - Cross Validated
Jun 25, 2018 · Feature, independent variable, explanatory variable, regressor, covariate, or predictor are all names of the variables that are used to predict the target, outcome, dependent variable, …
What are the differences between stochastic and fixed regressors in ...
What are the ramifications of this? > This has the basic implication that a sample with even one and varying deterministic regressor is no longer an identically distributed sample: 𝐸 (𝑦𝑖)=𝑏𝐸 (𝑥𝑖)+𝐸 (𝑢𝑖) 𝐸 (𝑦𝑖)=𝑏𝑥𝑖 and since …
What is the difference between Stochastic Regressor and Non …
Apr 28, 2016 · What is the difference between Stochastic Regressor and Non-Stochastic Regressor in Linear Regression? Ask Question Asked 9 years, 8 months ago Modified 8 years, 1 month ago
regression - Why is a random forest regressor better than a random ...
May 6, 2022 · However, looking at how to create a ml algorithm, it says that if the predicted output is a category a classification algorithm should be used. Hence I tried SVM, KNN, Random forest …
Log-Transforming target var for training a Random Forest Regressor
Feb 4, 2020 · Log transforming the var gives is a normal-like distribution. When training a Random Forest regressor on the non-transformed var, I get worse performance than when I log-tranform the …
regression - LightGBM Regressor miscalibratred/underestimating on …
Dec 13, 2023 · I'm training a pretty standard LightGBM regressor and noticing a strange pattern with the residuals (see images below--I'm bunching the predicted values and taking the observed average for …
What does it mean to regress a variable against another
Dec 4, 2014 · When we say, to regress Y Y against X X, do we mean that X X is the independent variable and Y the dependent variable? i.e. Y = aX + b Y = a X + b.
XGBRegressor score (R2) vs. eval_metric (RMSE) - Cross Validated
Jun 28, 2022 · According to the API Reference, XGBRegressor ().score () returns R2. However, according to the XGBoost Paramters page, the default eval_metric for regression is RMSE. In my …
multicollinearity - Interpreting Multicollinear Models with SHAP ...
Apr 8, 2025 · During inference, the isotonic regressor returns a calibrated probability based on the classifier's output. Here's the problem: some features in the classifier are highly correlated (0.5 - 0.7).
Should I choose Random Forest regressor or classifier?
Jan 5, 2017 · This page discusses the choice between Random Forest regressor and classifier, explaining their differences and when to use each.