# Tagged Questions

89 views

### What exactly is the equation for SVM classification for new example?

I understand that in the case of Logistic Regression, we simply multiply our weights with Input example for classification. But what exactly is the equation that we calculate in the case of SVM to ...
80 views

### In SVM, what are the labels and how do you get them from the data?

I'm working on a school project and have decided to use SVM for stock market prediction. I have a 1000x5 matrix of stock quotes containg data for open, close, high, low, volume data. From what I ...
145 views

### Support vector machines and Granger causality

I was wondering if Granger causality would be an efficient tool for searching for relevant input data for an SVM system. For example if I want to forecast SP 500 returns, I could put in my input data ...
160 views

### SVM and non-linear predictive models - feature selection

Just throwing out a general question. What do people think of applying feature selection methods when using SVMs to build predictive models? I understand that SVM have built in regularization with how ...
124 views

### Robust Support Vector Regression - robust to outliers

I've been reading/looking around for literature on support vector regressions that are relatively robust to outliers. I understand that standard SVRs can be significantly influenced by a few large ...
542 views

### Support vector regression on skewed/high kurtosis data

I'm using support vector regression to model some fairly skewed data (with high kurtosis). I've tried modeling the data directly but I'm getting erroneous predictions I think mainly due to the ...
184 views

### SVM parameter selection with NM simplex (or other algorithms)

I'm having some trouble getting the NM Simplex to find a good minimum for selecting hyperparameters of a rbf SVC. Not only am I tuning the 2 SVC parameters (C and gamma) I also have five class weights ...
183 views

### Non-linear regularized SVM implementation

Just a general question. Are there any good non-linear SVM (kernelized) implementations that include a regularization component (e.g. $L_1$, SCAD etc)? I've been looking around but man there are a lot ...
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### Non-linear (e.g. RBF kernel) SVM with SCAD penalties implementation

Is there one? I think there's a penalizedSVM package in R but it looks to use a linear kernel. Can't quite tell from the documentation. If it's linear, is there a R package that lets me calculate the ...
88 views

### General Non-linear Regularized Models

Had a general questions. Are there any good non-linear models with regularization? I've heard of some linear models with regularization but not too many non-linear ones. I understand that you can use ...
1k views

### Fastest SVM implementation

More of a general question. I'm running a rbf SVM for predictive modeling. I think my current program definitely needs a bit of a speed up. I use scikits learn with a coarse to fine grid search + ...
232 views

### Multiclass SVM + Ineffective X Validation, Time Series Prediction

I've recently run into an interesting and rather odd problem with cross validating a multiclass SVM that I can't figure out. Basically, I have a timeseries to predict and have created a dataset of ...
404 views

### Cross validation procedure - is this right?

Just want to check that I am performing my cross validation procedures right. I'm using a non-linear svm. I do a five fold cross validation (5 splits of test/train on my original training data) and ...
146 views

### SVM and cross validation with a minimum finding algorithm

Just a simple question on parameter selection for SVMs. If I use a minimum finding algorithm to find the optimal parameters for a set of data, how do I "average" the parameters over a set of cross ...
879 views

### SVM parameter selection and cross validation

Have a quick question about parameter selection for an SVM. I'm using a rbf kernel, so trying to optimize C and gamma. I have an example set of around 4500, about 700 features, and using 700 examples ...
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### Which performance measure to use when using SVM: MSE or MAE?

It is a common practice to measure an SVM model's performance by calculating its MSE (Mean Square Error). Why not use Mean Absolute Error (averaging errors' absolute values instead of squared values)? ...