Questions tagged [libsvm]
17 questions
2votes
1answer
18views
How to determine the feasible domain of a trained tree model?
As far as I know, tree models (such as those trained using xgboost/lightgbm) makes reasonable prediction only if the input feature vector is similar to the train set data. If the feature vector looks ...
1vote
0answers
188views
Using gpu accelerated libSVM in python
I have been using libSVM in python notebook to classify my dataset and it takes approximately 5 hours for one run and for 5 fold cross validation, it will take almost a day+ time. I am planning to ...
- 111
1vote
0answers
20views
How to normalize(or other) the audio data so that the same labels with the similar characteristics from different records?
I am trying to detect swallows from recordings taken from hospital. I manually labelled the recordings on the Praat. Now the valid labels are silence, swallows and nonswallows(noise, enviromenment ...
3votes
1answer
260views
Implementing a weighted support vector machine in python
I have the following problem. The minimization problem of the SVM that I want to solve is: $$ \min_{w, b} \frac{1}{2}w^{T}w + \sum^{m}_{i=1}C_{i}xi_{i} $$ Subject to: $$ y_{i}(w^{T}x_{i} - b) \geq 1 - ...
- 33
3votes
1answer
2kviews
Convert Pandas Dataframe with mixed datatypes to LibSVM format
I have a pandas data frame with about Million rows and 3 columns. The columns are of 3 different datatypes. NumberOfFollowers is of a numerical datatype, UserName is of a categorical data type, ...
- 359
0votes
1answer
213views
SVM SVC: Metric for parameter optimization on imbalanced data
I trained a multiclass SVC with RBF kernel on a down-sampled (and therefore balanced) dataset. Now I want to perform grid search to find best cost and gamma. What performance metric should I optimize ...
- 55
1vote
0answers
26views
Practical examples/tutorials of using One-Class Support Vector Machines
I am a newbie in machine learning, and hope to solve an anomaly detection task using One-Class Support Vector Machines (OCSVM). ...
- 121
0votes
1answer
1kviews
Linear SVM in matlab and python giving different results
I have a particular dataset on which I am getting different results when using a linear SVM in matlab and sklearn toolbox. The data has been normalized in matlab and imported into python from a mat ...
- 21
2votes
1answer
2kviews
Why Liblinear performs drastically better than libsvm linear kernel?
l have a dataset of dim=(200,2000) 200 examples and 2000 features. l have 10 classes. l used sklearn for both cases : svm.svc(kernel=linear) LinearSVC() ...
- 225
4votes
1answer
6kviews
What is the difference between Linear SVM and SVM with linear kernel?
I'm wondering whether there is a difference between Linear SVM and SVM with a linear kernel. Or is a linear SVM just a SVM with a linear kernel? If so, what is the difference between the two ...
- 225
-2votes
1answer
2kviews
Where can I find python code for SVM that use multiple feature data? [closed]
I am trying do an Image Classification where each sample of training data contains data of the current pixel with the 8 surrounding ones. Where can I find examples of SVM, in python, that use 5 or ...
- 143
2votes
0answers
62views
Obtain standard deviation for libsvm
I have the following code for Grid search, but it only return the accuracy result using 5 folds cross-validation. Is it possible to obtain standard deviation from the 5 folds CV. How would you do that?...
- 31
0votes
2answers
4kviews
Is standardization needed before using scikit-learn SVM?
I am using the SVM function provided by scikit-learn. I would like to know whether I need to perform standardization before fitting the model. As I know, LibSVM ...
- 253
1vote
0answers
92views
$\chi^{2}$ kernel SVM performance issue
I am using $\chi^{2}$ kernel for non-linear SVM (using libSVM) for classifying MNIST digits. I am getting very bad performance (worse than random guessing). The $\chi^{2}$ kernel code (in MATLAB) is ...
- 3,855
2votes
2answers
287views
Prepare data for SVM, Is it valid to normalise the data before and after PCA dimension reduction
Is it valid to normalise a dataset, reduce dimensionality with PCA and then to normalise the reduced dimension data. Assuming this is performed on training data, should the same PCA coefficients be ...
- 21
