bayesian | 易学教程

Hyperparameter optimization for Deep Learning Structures using Bayesian Optimization

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I have constructed a CLDNN (Convolutional, LSTM, Deep Neural Network) structure for raw signal classification task. Each training epoch runs for about 90 seconds and the hyperparameters seems to be very difficult to optimize. I have been research various ways to optimize the hyperparameters (e.g. random or grid search) and found out about Bayesian Optimization. Although I am still not fully understanding the optimization algorithm, I feed like it will help me greatly. I would like to ask few questions regarding the optimization task. How do I set up the Bayesian Optimization with regards to a

Incremental model update with PyMC3

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问题 Is it possible to incrementally update a model in pyMC3. I can currently find no information on this. All documentation is always working with a priori known data. But in my understanding, a Bayesian model also means being able to update a belief. Is this possible in pyMC3? Where can I find info in this? Thank you :) 回答1: Following @ChrisFonnesbeck's advice, I wrote a small tutorial notebook about incremental prior updating. It can be found here: https://github.com/pymc-devs/pymc3/blob/master

What is a better way to sort by a 5 star rating?

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I'm trying to sort a bunch of products by customer ratings using a 5 star system. The site I'm setting this up for does not have a lot of ratings and continue to add new products so it will usually have a few products with a low number of ratings. I tried using average star rating but that algorithm fails when there is a small number of ratings. Example a product that has 3x 5 star ratings would show up better than a product that has 100x 5 star ratings and 2x 2 star ratings. Shouldn't the second product show up higher because it is statistically more trustworthy because of the larger number

What is a better way to sort by a 5 star rating?

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问题 I\'m trying to sort a bunch of products by customer ratings using a 5 star system. The site I\'m setting this up for does not have a lot of ratings and continue to add new products so it will usually have a few products with a low number of ratings. I tried using average star rating but that algorithm fails when there is a small number of ratings. Example a product that has 3x 5 star ratings would show up better than a product that has 100x 5 star ratings and 2x 2 star ratings. Shouldn\'t the

Hyperparameter optimization for Deep Learning Structures using Bayesian Optimization

阅读更多关于 Hyperparameter optimization for Deep Learning Structures using Bayesian Optimization

问题 I have constructed a CLDNN (Convolutional, LSTM, Deep Neural Network) structure for raw signal classification task. Each training epoch runs for about 90 seconds and the hyperparameters seems to be very difficult to optimize. I have been research various ways to optimize the hyperparameters (e.g. random or grid search) and found out about Bayesian Optimization. Although I am still not fully understanding the optimization algorithm, I feed like it will help me greatly. I would like to ask few