Table 2. The classification accuracy/AUC of 25 WEKA classifiers using combined multi-parametric histogram and texture attributes in LGG and HGG as well as grade II, III and IV gliomas classification.
| 25 WEKA classifiers (accuracy/AUC) | LGG vs. HGG | Grade II, III and IV | |||
|---|---|---|---|---|---|
| Original (28 vs. 92) | Smote (100 vs. 100) | Original (25 vs. 29 vs. 63) | Smote (68 vs. 68 vs. 68) | ||
| Bayes | BayesNet | 0.717/0.743 | 0.750/0.826 | 0.667/0.836 | 0.770/0.880 |
| NaiveBayes | 0.742/0.717 | 0.845/0.874 | 0.641/0.778 | 0.750/0.885 | |
| Lazy | IBk## | 0.750/0.638 | 0.905/0.905 | 0.718/0.795 | 0.961##/0.971 |
| LWL | 0.733/0.769 | 0.800/0.833 | 0.735/0.858 | 0.642/0.892 | |
| Functions | LibSVM (linear)** # | 0.792/0.690 | 0.945*/0.945 | 0.786#/0.838 | 0.956/0.957 |
| Logistic | 0.708/0.698 | 0.885/0.934 | 0.556/0.716 | 0.828/0.895 | |
| SimpleLogistic | 0.792/0.841 | 0.930/0.957 | 0.735/0.888 | 0.922/0.976 | |
| SGD | 0.792/0.715 | 0.930/0.930 | 0.701/0.816 | 0.917/0.977 | |
| SMO**# | 0.758/0.668 | 0.945*/0.945 | 0.786#/0.874 | 0.956/0.975 | |
| VotedPerceptron | 0.758/0.697 | 0.800/0.861 | 0.590/0.758 | 0.657/0.873 | |
| Meta | AdaBoostM1* | 0.808*/0.793 | 0.875/0.956 | 0.675/0.925 | 0.809/0.894 |
| Bagging | 0.783/0.818 | 0.855/0.933 | 0.726/0.912 | 0.858/0.966 | |
| ClassificationViaRegression | 0.708/0.800 | 0.830/0.900 | 0.658/0.879 | 0.939/0.843 | |
| LogitBoost* | 0.808*/0.846 | 0.885/0.945 | 0.675/0.891 | 0.877/0.974 | |
| Rules | Decision Table | 0.642/0.597 | 0.795/0.896 | 0.761/0.912 | 0.745/0.871 |
| Jrip | 0.767/0.612 | 0.850/0.808 | 0.726/0.838 | 0.814/0.879 | |
| OneR | 0.792/0.616 | 0.645/0.645 | 0.718/0.809 | 0.672/0.754 | |
| PART | 0.633/0.567 | 0.830/0.804 | 0.692/0.821 | 0.775/0.818 | |
| Trees | DecisionStump | 0.767/0.629 | 0.815/0.630 | 0.726/0.771 | 0.304/0.608 |
| HoeffdingTree | 0.742/0.218 | 0.850/0.875 | 0.650/0.777 | 0.750/0.885 | |
| J48 | 0.675/0.397 | 0.855/0.801 | 0.684/0.817 | 0.833/0.872 | |
| LMT | 0.800/0.849 | 0.930/0.958 | 0.744/0.896 | 0.922/0.976 | |
| RandomForest | 0.792/0.845 | 0.915/0.976 | 0.752/0.892 | 0.922/0.984 | |
| RandomTree | 0.658/0.540 | 0.815/0.813 | 0.607/0.698 | 0.755/0.818 | |
| REPTree | 0.742/0.460 | 0.820/0.850 | 0.650/0.837 | 0.779/0.901 | |
*, ** represent the classifier with the highest classifying accuracy on original and SMOTE LGG and HGG glioma data, respectively. #, ## represent the classifier with the highest classifying accuracy on original and SMOTE grade II-III-IV glioma data, respectively.