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Knowledge Graphs: Opportunities and Challenges
With the explosive growth of artificial intelligence (AI) and big data, it has become vitally important to organize and represent the enormous volume of knowledge appropriately.
Combination of PCA with SMOTE Resampling to Boost the Prediction Rate in Lung Cancer Dataset
In the first step PCA is applied on Lung-Cancer dataset to compact the dataset and eliminate irrelevant features and in the second step SMOTE resampling is carried out to balance the class distribution and increase the variety of sample domain.
A Hybrid Feature Selection Method to Improve Performance of a Group of Classification Algorithms
In this paper a hybrid feature selection method is proposed which takes advantages of wrapper subset evaluation with a lower cost and improves the performance of a group of classifiers.
Improving Performance of a Group of Classification Algorithms Using Resampling and Feature Selection
Finally, we apply some well- known classification algorithms (Na\"ive Bayes, Logistic, Multilayer Perceptron, Best First Decision Tree and JRIP) to the resulting dataset and compare the results and prediction rates before and after the application of our feature selection method on that dataset.
