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Questions tagged [ensemble-modeling]

In machine learning, ensemble methods combine multiple algorithms to make a prediction. Bagging, boosting, and stacking, are some examples.

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1answer
689 views

Pick a model from multiple models using a decision tree

Let us say, I have 4 classification models on a training data set of various examples. Now, I want to choose which 1 out 4 models (or what combination of the 4 ...
6
votes
1answer
9k views

Assumptions/Limitations of Random Forest Models

What are the general assumptions of a Random Forest Model? I could not find by searching online. For example, in a linear regression model, limitations/assumptions are: It may not work well when ...
4
votes
2answers
1k views

How to ensemble classifier incorporating all features in python?

I am doing a text classification task(5000 essays evenly distributed by 10 labels). I explored LinearSVC and got an accuracy of 80%. Now I guess whether accuracy ...
7
votes
2answers
212 views

Why isn't dimension sampling used with gradient boosting machines (GBM)?

GBMs, like random forests, build each tree on a different sample of the dataset and hence, going by the spirit of ensemble models, produce higher accuracies. However, I have not seen GBM being used ...

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