Questions tagged [ensemble-learning]

For questions related to ensemble learning, which refers to machine learning techniques where multiple models (e.g. a neural network and a decision tree) are trained and their predictions are combined to solve the same problem. Bagging and boosting are two popular ensemble learning techniques.

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When do two identical neural networks have uncorrelated errors?

In Chapter 9, section 9.1.6, Raul Rojas describes how committees of networks can reduce the prediction error by training N identical neural networks and averaging the results. If $f_i$ are the ...
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51 views

When do the ensemble methods beat neural networks?

In many applications and domains, computer vision, natural language processing, image segmentation, and many other tasks, neural networks (with a certain architecture) are considered to be by far the ...
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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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23 views

Would performance of atomic models matter in ensemble methods?

Suppose I have two fitted ensemble models $F_1 := (f_1, f_2, f_3, \cdots f_n)$ and $G_1 := (g_1, g_2, g_3, \cdots g_n)$. And they were using the same ensemble methods (boosting or bagging). And I am ...
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21 views

How can we combine different deep learning models?

I know that ensembles can be made by combining sklearn models with a VotingClassifier, but is it possible to combine different deep learning models? Will I have to make something similar to Voting ...
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1answer
35 views

Is there an approach where the output of one neural network is used to choose the next neural network?

I'd like to design a deep learning architecture in which the output of a primary neural network $M_{\theta}$ determines which neural network $N^i_{\alpha}$ in a set of secondary networks $\mathcal{N}$ ...
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16 views

How to improve the PMI (Pointwise Mutual Information) Quality for document based PMI

Generating word embeddings from the PMI is well understood and known to be equivalent to SGNS (skipgram negative-sampling) under certain conditions. I was able to get good quality word embedding using ...
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19 views

How to ensemble two different computer vision models?

I have prepared two distinct models: Representing contour of the image Representing edges of the image. I would like to create a model which can take advantage of both models in predicting data. May ...
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28 views

How to make an LSTM ensemble model with different input shapes

This is what I got so far for making an lstm ensemble with one model input for each of the lstm models and for the ensemble model and it works perfectly. ...
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0answers
169 views

How to make an ensemble model of two LSTM models with different window sizes i.e. different data shapes

Below is the Python code for making an ensemble model. All the inputs are the same for all three models. But what if the models have different input shapes due to different window size, such as LSTM ...
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1answer
38 views

Why does the error ensemble use the ceiling of the number of classifiers?

What is $y$? Why is $k$ the ceil of $n/2$? What is $y \geq k$?