The hyperparameter tag has no wiki summary.
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Parameter learning of Markov random field
Given a Markov random field $\mathcal{G} = (\mathcal{V},\mathcal{E})$, the corresponding density function to which is expressed by
$f(x) \propto \prod_{x\in\mathcal{V}} \psi_u(x) ...
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Rule of thumb for tuning the values of the penalty parameter in SVM models
I have recently been running into computational issues in fitting a soft-margin SVM model using the e1071 package in R.
The issue is unavoidable since the problem ...
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What is the correct way of implementing weight decay?
When applying weight decay, does one just use all available input features, an arbitrary large number of hidden layer nodes, and cross validate for the appropriate weight decay parameter? Or what is ...
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About SVM cost and gamma parameters tuning
I am using R and e1071 package to tune a C-classification SVM.
My question is: regardless of the kernel type (linear, ...
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Random search for the optimal number of input features and optimal number of hidden layers for a MLP?
I've preformed a random search in the hypothesis space $$\{(c,h)| c \in U[1,256]; h\in U[1,100];c \in \mathrm{Z} \text{ and } h \in \mathrm{Z}\}$$ that defines the parameters of a standard MLP neural ...
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Selecting optimal number of input features and optimal number of hidden layers for a MLP?
What is the best way to select parameters for a binary neural network classifier? More specifically I have 265 features ranked according to Mutual Information Criterion. I have to determine the ...
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How to optimize hyper-parameters in LDA?
After reading Hanna Wallach's paper Rethinking LDA: Why Priors Matter, I want to add hyper-parameter optimization to my own implementation of LDA. However, the paper doesn't given any details about ...
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201 views
Estimating hyperparameter in basis functions (Gaussian and sigmoid) for linear regression
I am working on a linear regression problem with Gaussian and sigmoid basis functions. My data set is very large, say a total of 15K inputs with each input having 46 features. I have divided my data ...
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Natural interpretation for LDA hyperparameters
Can somebody explain what is the natural interpretation for LDA hyperparameters? ALPHA and BETA are parameters of Dirichlet ...
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Trouble minimizing perplexity in LDA
I am running LDA from Mark Steyver's MATLAB Topic Modelling toolkit on a few Apache Java open source projects. I have taken care of stop word removal (for e.g. words such Apache, java keywords are ...
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How to use multiple datasets in order to measure the performance of a learning system?
I’m working on a project where I need to test a machine learning system which has a lot of hyper-parameters. Further, in order to gauge the performance of system, I’m planning to use several ...
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Hyper-parameter optimization via random search
I’m working on a classification system which consists of an auto-encoder for feature learning and logistic regression for classification. The system has five hyper-parameters as enumerated below.
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Bias in classifier model selection
Say I have a set of classifier models, each generated using feature selection inside a repeated k-fold cross-validation. Each classifier model is generated using a different set of regularization ...
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454 views
Hyperparameter estimation in gaussian process
Dear gaussian process experts,
i'm trying to optimize the hyperparameters for a gaussian process. As a starter i choose the squared exponential formula for covariance where i have to optimize 3 ...
