Questions tagged [boosting]
For questions related to the concept of boosting in machine learning, which is a collection of ensemble learning methods.
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Confusion about the code for choosing "stumps" in Adaboost algorithm
(I actually asked the following question on Stack Overflow and Cross Validated Exchange for more than a month:
https://stackoverflow.com/questions/76842431/confusion-about-the-code-for-choosing-...
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How do we determine what is correct and what not in Adaboost
In Adaboost, how is it determined what is correct and what not?
In the following example from StatQuest (in youtube), what correct is
and what incorrect makes sense in real life. But what if we have a ...
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Can i train xgboost on multiple time series csv files at the same time?
I built an xgboost model to predict stock it now trains on 1 stock at a time its a csv file I use pandas to load it.
Is there a way to train the model on multiple stocks at the same time? What would ...
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How to specify categorical features in cat boost?
I have a dataset (pandas data frame) with all features of type int32 containing continuous values except one feature state_number, its data type is int32, but it ...
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Multiclass Ensemble Methods with weak classifiers under 50%
Normally, when using an ensemble method, such as baggin or boosting, in binary classification, there is a reqauirment that each weak classifier have accuracy better than 50%.
In the multiclass ...
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What ensemble methods are used in the state-of-the-art models?
What ensemble methods are used in the state-of-the-art models?
When I surveyed the state-of-the-art methods of classification and detection, e.g. ImageNet, COCO, etc., I noticed that are few or even ...
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Why don't ensembling, bagging and boosting help to improve accuracy of Naive bayes classifier?
You might think to apply some classifier combination techniques like ensembling, bagging and boosting but these methods would not help. Actually, “ensembling, boosting, bagging” won’t help since their ...
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How do weak learners become strong in boosting?
Boosting refers to a family of algorithms which converts weak learners to strong learners. How does it happen?
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Are there tabular datasets where deep neural networks outperform traditional methods?
Are there (complex) tabular datasets where deep neural networks (e.g. more than 3 layers) outperform traditional methods such as XGBoost by a large margin?
I'd prefer tabular datasets rather than ...
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Why would the application of boosting prevent underfitting?
"Why would the application of boosting prevent underfitting?"
I read in some paper that applying boosting would prevent you from underfitting. Why is that?
Source:
https://www.cs.cornell.edu/...
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