'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), kernels)
plt.title('P values for each svm kernel')
plt.xlabel('SVM kernel')
plt.ylabel('P values Rate')
plt.ioff()
plt.savefig('images/pValues.png')
plt.show()
Which one of the algorithms do we consider the best (in t-values and p-values) and why? Is it the nearest to 1 or the nearest to 0?
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