Questions tagged [stacking]
The stacking tag has no usage guidance.
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Stacking realization problems
I have two dataframes: x_train with features got from base models and y_train with ground true labels of these features using cross_validation.
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Understanding of stacking
I use various autoML solutions so I can't stack my models directly (for example via StackingClassifier, mlextend or as layers in keras) so I want to implement my own pipeline for this case using only ...
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Feature Importance in Stacked Model
I have built a stacked model using mlxtend StakingCVClassifier. I want to know the feature importance scores now. Is there any way I can calculate feature importance scores for the stacked model? If ...
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Fit multiple models e.g classifiers -> stacking -> calibration without data-leak or getting too many datasets
I have some data X on which I want to do the following:
Train two models; SVM and Logistic Regression
Use a stacking classifier based on the models from (1)
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Stacking vs Blending. Why ever use blending?
If I understand correctly, stacking uses a set of "level 1" models, creates out of fold predictions and then trains these models on the full training data. The out of fold predictions are ...
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KeyError: 'Resize' Error in converting from ONNX model to keras
I am trying to convert an ONNX model to a Keras model using onnx2keras, so that I can implement this: (https://machinelearningmastery.com/stacking-ensemble-for-deep-learning-neural-networks/) stacking ...
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Stacking: Use predictions of train or test to create features for level 1 classifier
The question is pretty simple.
In stacking, the predictions of level 0 models are being used as features to train a level 1 model.
However, the predictions of what data? Intuitively it makes more ...
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Feature Selection using Stacking Ensemble?
I want to combine some estimators, such as Logistic Regression, Gaussian NB and ...
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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 ...
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How to use SMOTE in Stacking in SKLearn?
I have a data set X,y and split them to train and test data.
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How does stacking help Bias and Variance?
How does stacking help in terms of bias and variance?
I have a hunch that stacking can help reduce bias but i am not sure, could someone refer to a paper?
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Feature importance difference in two similar machine learning models
Situation 1:
I have trained a text classification model (Model 1) which gives me a probability of true class as X. I have also trained a classification model (Model 2) using only the categorical and ...
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Stacking: How to best treat base learner?
With stacking, several (diverse) base learners are used to predict the dependent variable $\hat{y}_{b,m}=\beta_{b,m} X$ in a hold-out set, where $m$ are base learner models $1,...,n$. These ...
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What kind of algorithms can be used as a stacker in stacked generalization?
In stacked generalization, several algorithms (I use some random trees, booster trees, etc.) are first trained and used to make the predictions which are used as input for another algorithm. However, ...
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