Questions tagged [bagging]

The tag has no usage guidance.

Filter by
Sorted by
Tagged with
2
votes
1answer
27 views

Can Boosting and Bagging be applied to heterogeneous algorithms?

Stacking can be achieved with heterogeneous algorithms such as RF, SVM and KNN. However, can such heterogeneously be achieved in Bagging or Boosting? For example, in Boosting, instead of using RF in ...
0
votes
1answer
13 views

Difference between bagging and pasting?

I found the definition: ...
0
votes
0answers
4 views

How to apply feature selection in cross validated bagging

Normally in cross validation decision tree, feature selection will occur with training data but in bagging ensemble the training data is bootstrapped. How can I apply feature selection in cross ...
1
vote
1answer
23 views

Base model in ensemble learning

I've been doing some research on ensemble learning and read that for base models, model with high variance are often recommended (can't remember which book I read this from exactly). But, it seems ...
2
votes
1answer
17 views

bagging vs. pasting in ensemble learning

I am bit confused about two concepts. From my understanding Bagging is when each data is replaced after each choice. so for example for each subset of data you pick one from population, replace it ...
0
votes
1answer
19 views

Bagging Base models

If bagging reduces overfitting than the general statement that base learners of ensemble models should have high bias and low variance(that is should be undefiting) wrong?
0
votes
1answer
38 views

Why the accuracy of my bagging model heavily affected by random state? [closed]

The accuracy of my bagging decision tree model reach up to 97% when I set the random seed=5 but the accuracy reduce to only 92% when I set random seed=0. Can someone explain why the huge gap and ...
1
vote
1answer
44 views

Counting the number of trainable parameters in a gradient boosted tree

I recently ran the gradient boosted tree regressor using scikit-learn via: GradientBoostingRegressor() This model depends on the following hyperparameters: Estimators ($N_1$) Min Samples Leaf ($N_2$...
2
votes
1answer
28 views

Can I do bagging method as improvement technique to decision tree in research?

Bagging use decision tree as base classifier. I want to use bagging with decision tree(c4.5) as base as the method that improve decision tree(c4.5) in my research that solve problem overfitting. Is ...
3
votes
0answers
64 views

Difference Bagging and Bootstrap aggregating

Bootstrap belongs to Efron. Tibshirani wrote a book about that in reference to Efron. Bootstrap process for estimating the standard error of statistic s(x). B bootstrap sample are generatied from ...
1
vote
1answer
39 views

How does bagging help reduce the variance

I learned that bagging helps reduce variance by averaging but I couldn't understand this. Can someone explain this intuitively?
1
vote
0answers
53 views

Can bagging ensemble consist of heterogeneous base models?

Bagging or bootstrap aggregation seems to make sense for time series forecasting using an ensemble because bagging randomizes subsets of the data with replacement. However, I've only seen bagging used ...
2
votes
1answer
36 views

Random Forest Stacking Experiment for Imbalanced Data-set Problem

In order to solve a Imbalanced Dataset Problem, I experimented with Random Forest in the given manner (Somewhat inspired by Deep-Learning) Trained a Random Forest which will take in the input data ...
3
votes
1answer
94 views

Bagging vs pasting in ensemble learning

This is a citation from "Hands-on machine learning with Scikit-Learn, Keras and TensorFlow" by Aurelien Geron: "Bootstrapping introduces a bit more diversity in the subsets that each predictor is ...
6
votes
1answer
450 views

Boosting with highly correlated features

I have a conceptual question. My understanding is, that Random Forest can be applied even when features are (highly) correlated. This is because with bagging, the influence of few highly correlated ...