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A tutorial here details how ensembles can be created using scikit-learn:
https://towardsdatascience.com/ensemble-learning-using-scikit-learn-85c4531ff86a?gi=f8603ef652d0
After you have a predict…
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Here's a quick implementation of classical conditioning that's pretty much the same as the model in DAC and other places. The idea is that the cerebellum is a forward model that takes all the stimuli…
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Post questions here about:
Witten, Ian H., Eibe Frank, Mark A. Hall, Christopher J. Pal. 2017. [“Ensemble Learning”](https://github.com/Computational-Content-Analysis-2020/Readings-Responses/files/…
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Would it be possible to implement an encoder learning rule in Nengo that uses the backprop learning rule? Or even the feedback alignment learning rule (which is basically just backprop but with a ran…
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Four keypoints:
1. Learning Dynamics.
- Firstly try: Ensemble Dynamics using MSE. (MB-MPO)
- Then, try RNN.
- Model uncertainty: MDN or GANonZ , on 1234 dataset.
- Afterwards: Use …
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hi ,i am a newbie in deeplearning,when i read your paper (Stochastic Multiple Choice Learning for Training Diverse Deep Ensembles),i think it is useful for me ,but i can not design in myself,can you s…
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### Describe the bug
I am working on a multilabel classification problem using ClassifierChain with RandomForestClassifier as the base estimator.
I have encountered an issue where ClassifierChain …
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For my data, I got the best pipeline by running TPOT training using the following parameters:
```python
from tpot import TPOTClassifier
tpot = TPOTClassifier(generations=5,
…
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Machine Learning is a common tool to apply to time-domain data in astronomy. We should work to understand what supporting ML workflows could look like in TAPE, whether it's simply ensuring our ensembl…
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https://github.com/nengo/nengo-fpga/blob/a19a29ad6d735a1390a699f5f5cc88896ff0227f/nengo_fpga/networks/fpga_pes_ensemble_network.py#L185-L188
A synapse (that is not directly configurable) is created…