Category "svm"

Poor accuarcy score for Semi-Supervised Support Vector machine

I am using a Semi-Supervised approach for Support Vector Machine in Python for the image classification from PASCAL VOC 2007 data. I have tried with the default

Plot scikit-learn (sklearn) SVM decision boundary / surface

I am currently performing multi class SVM with linear kernel using python's scikit library. The sample training data and testing data are as given below: Mode

SKLearn: Getting distance of each point from decision boundary?

I am using SKLearn to run SVC on my data. from sklearn import svm svc = svm.SVC(kernel='linear', C=C).fit(X, y) I want to know how I can get the distance of

Number of Support vectors in SVM

How do I print the number of support vectors for a particular SVM model? Please suggest a code snippet in Python. from sklearn.multiclass import OneVsRestClassi

Which algorithm is the best based on P-Values

I used the following code: plt.figure(figsize = (7, 7)) plt.boxplot([totalP['poly'], totalP['rbf'], totalP['linear'], totalP['gf']]) plt.xticks(np.arange(1, 5),

Support Vector Machine library for C# [closed]

Is there any Support Vector Machine library already implemented which I could use in my C# projects?

Scikit Learn SVC decision_function and predict

I'm trying to understand the relationship between decision_function and predict, which are instance methods of SVC (http://scikit-learn.org/stable/modules/gene

Speeding up grid search in sklearn

I am performing a grid search to identify the best SVM parameters. I am using ipython and sklearn. The code is slow and runs on only one core. How can this be s

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