machine learning - What exactly is min_samples_leaf in scikit-learn's ...
Jun 11, 2022 · machine-learning random-forest hyperparameter Improve this question asked Jun 10, 2022 at 17:00 NaiveBae
Is Random Forest suitable for very small data sets?
Typically the one restriction on random forest is that your number of features should be quite big - the first step of RF is to choose 1/3n or sqrt (n) features to construct a tree (depending on task, …
Why is pruning not needed for random forest trees?
25 Breiman says that the trees are grown with out pruning. Why? I mean to say that there must be a solid reason why the trees in random forest are not pruned. On the other hand it is considered very …
machine learning - Difference between Random Forest and Extremely ...
I understood that Random Forest and Extremely Randomized Trees differ in the sense that the splits of the trees in the Random Forest are deterministic whereas they are random in the case of an Extr...
r - Random forest vs regression - Cross Validated
Dec 18, 2015 · The independent variables and dependent variable are both continuous and are linearly related. The R Square is about 99.3%. But when I run the same using random forest in R my result is …
Random Forest - How to handle overfitting - Cross Validated
Aug 15, 2014 · To avoid over-fitting in random forest, the main thing you need to do is optimize a tuning parameter that governs the number of features that are randomly chosen to grow each tree from the …
python - difference between sample_weight and class_weight …
Nov 7, 2016 · You are using the sample_weights wrong. What you want to use is the class_weights. Sample weights are used to increase the importance of a single data-point (let's say, some of your …
Using a Random Forest for Time Series Data - Cross Validated
Dec 29, 2018 · A random forest would not be expected to perform well on time series data for a variety of reasons. In my view the greatest pitfalls are unrelated to the bootstrapping, however, and are not …
Difference between regression and classification for random forest ...
May 28, 2021 · The Random forest method is an ensemble method that consists of multiple decision trees and is used for both regression and classification. A decision tree is a very simple technique …
How to interpret OOB and confusion matrix for random forest?
How to interpret OOB and confusion matrix for random forest? Ask Question Asked 13 years, 8 months ago Modified 9 years, 7 months ago