Questions tagged [ensemble]

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1answer
13 views

Physical modelling with neural networks - single output + stack ensemble vs multi-output

We are trying to replace an existing physical model (8 inputs/7 outputs) with artificial neural networks. The physics behind the existing model is mainly thermodynamics of humid air for air ...
0
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1answer
39 views

Handling Categorical Features on NGBoost

Recently I have been doing some research on NGBoost, but I could not see any parameter for categorical features. Is there any parameter that I missed? ...
1
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1answer
21 views

What should I use as training data for base (level 1) classifiers in ensembling?

Can I just take all training data that I have, train the base models on them and then take their results and use them for training level 2 model? Is this a good practice, or should it be done ...
2
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1answer
57 views

What is the difference between horizontal and vertical ensemble?

I am looking at different ways to do model ensembling and I came across the terms horizontal and vertical blending/ensembling but it is not well defined. My questions will be: What is the ...
1
vote
1answer
38 views

grid search - optimal weighting of classifiers

i am using three different of the shelf classifiers. it`s a three class classification task. i want to calculate the optimal weights (c1weight, c2weight, c3weight) for each classifier (real task more ...
0
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1answer
22 views

How can the Adaboost technique be called an ensemble learning technique?

I have read that in ensemble learning we use the outputs of various classifiers to make the predictive modeling better but in Adaboost we just use one classifier and we make it a strong learner but ...
0
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0answers
57 views

Why are deep ensembles and monte carlo dropout never used simultanuously in uncertainty estimation

In papers on this topic, I have seen deep ensembles being compared to dropout monte carlo. I was wondering why they are never used simultanously, since adding dropout monte carlo to every member of an ...
0
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0answers
9 views

How to weight models for ensemble learning where models dont always have an output?

I have a problem, where I need to weight models for ensemble learning, however, some models aren't always able to give a prediction. The problem to classify 1 unit to win out of several ( 5 - 10 other ...
1
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1answer
43 views

How can I make ROC and compute AUC?

I created a boosting tree and got the probability for each tuple in my testing set. But I'm confused on how to combine each probability. Can someone tell me how to combine the probabilities?
1
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2answers
198 views

Combining Classifiers with different Precision and Recall values

Suppose I have two binary classifiers, A and B. Both are trained on the same set of data, and produce predictions on a different (but same for both classifiers) set of data. The precision for A is ...
2
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1answer
62 views

When and how to use bagging?

Can all types of ML methods benefit from bagging? Decision Tree Classification seems always be the go-to example of bagging, what about other classifiers or regressions? When it's suitable to do ...
1
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2answers
180 views

How to visualize Ensemble Models ( Random Forest) with 1000 estimators

I am working on classification problem where I need to categorize the user in buy/ non-buy category. I have around 100 + features or predictors to predict the behavior of user. I tried to implement ...
1
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0answers
373 views

How to create an ensemble in tensorflow using tf.estimator?

I have created a neural network using tensorflow's estimator API: ...
2
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2answers
174 views

xgboost cannot identify perfectly fitting regression line

For a dataset I want to use xgboost for the optimal ensembling of $n$ forecasts instead of just using their arithmetic mean for combination. I found that xgboost generates forecasts that are worse ...
3
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0answers
67 views

Gridsearch XGBoost for ensemble. Do I include first-level prediction matrix of base learners in train set?

I'm not quite sure how I should go about tuning xgboost before I use it as a meta-learner in ensemble learning. Should I include the prediction matrix (ie. df containing columns of prediction results ...
4
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1answer
639 views

Geometric and harmonic means in ensembling methods

When using ensembling methods for regression, a common approach is to average (using the arithmetic mean) the outputs of the weak learners in order to obtain the output of the ensemble. Is there a ...
3
votes
1answer
129 views

Methods for ensembling ranked lists?

I was wondering if there's a good way to use ensembling when I have two or more algoritims producing ranked lists. That is, suppose I have the following datasets consisting of ordered lists (higher ...
2
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2answers
164 views

How to create an ensemble that gives precedence to a specific classifier

Suppose that in a binary classification task, I have separate classifiers A, B, and C. If I ...
2
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1answer
77 views

Can clustering my data first help me learn better classifiers?

I was thinking about this lately. Let's say that we have a very complex space, which makes it hard to learn a classifier that can efficiently split it. But what if this very complex space is actually ...