Logistic Regression Svm Comparison. The machine learning algorithms used were compared based on accuracy processing time and receiver operating characteristic ROC values. Logistic Regression Vs Decision Trees Vs SVM.
Which One is Better to Discriminate. And compared with the algorithms which have higher. The main purpose of a classification algorithm is to figure out the estimator for the decision boundary.
In spite of the name logistic regression this is not used for regression.
A priori selection of core brain regions also improved classifier performance for LR and SVM models especially when combined with tSNE. Multinomial logistic regression MLR and na ıve Bayes NB were used. Compared with simple algorithms such as decision tree and naive Bayes classification logistic regression has higher accuracy 20. Comparison between SVM and Logistic Regression.