Sentence examples for compared feature from inspiring English sources

However, Random forest gives highest classification accuracy than all other compared feature selection methods.

Extensive empirical results demonstrate the advantage of MDFS over several compared feature selection methods.

However, the classification accuracy given by the proposed method with random forest classifier is almost similar to other compared feature selection methods.

Similarly, in case of Iris, Monk1, Monk2, Monk3, Tic-Tac-Toe and Zoo datasets, average accuracy found on the proposed method with different classifiers is lower than other compared feature selection methods.

One can observe that the proposed method achieved higher validation accuracy (0.81) than all other compared feature selection approaches, while using the lowest number of features in the final prediction model.

In Wine dataset, the average classification accuracy found on EFS-MI with decision trees, random forest and SVM is better than all the compared feature selection methods except for chisqure.

As shown in Table 3, in the breast cancer and colon cancer datasets, the proposed method yields high classification accuracy with decision trees, random forest, KNN and SVM classifiers than all the compared feature-selection methods in both the datasets.

Hu et al. [8] compared the most common features used in source camera identification and obtained 92% accuracy when combining all compared features.

Circuit models are then used to estimate the dynamic and leakage power consumption of the compared features.

Next we compared features of entire songs, (eg the total number of phrases, the number of buzzes etc).

Experimental results show that the proposed algorithms (GM-SMCC and EGM-SMCC) can lead to performance superior to other compared feature-based approaches, graph-based approaches, and collective classification algorithms.