# QFC: A Parallel Software Tool for Feature Construction, Based on Grammatical Evolution
## 4 Experiments
### Experimental Datasets  
The validity of the method was tested on a series of well-known datasets from the relevant literature. The main repositories for the testing were:  
1. The UCI Machine Learning Repository [[http://www.ics.uci.edu/~mlearn/MLReposiory.html](http://www.ics.uci.edu/~mlearn/MLReposiory.html)]([http://www.ics.uci.edu/~mlearn/MLReposiory.html](http://www.ics.uci.edu/~mlearn/MLReposiory.html)) (accessed on 18 August 2022)
2. The Keel repository [[https://sci2s.ugr.es/keel/](https://sci2s.ugr.es/keel/)]([https://sci2s.ugr.es/keel/](https://sci2s.ugr.es/keel/)) (accessed on 18 August 2022)
3. The Statlib repository [[http://lib.stat.cmu.edu/datasets/](http://lib.stat.cmu.edu/datasets/)]([http://lib.stat.cmu.edu/datasets/](http://lib.stat.cmu.edu/datasets/)) accessed on 18 August 2022). The classification datasets are:  
1. **Australian** dataset [66], a dataset related to credit card applications. 2. **Alcohol** dataset, a dataset about Alcohol consumption [67]. 3. **Balance** dataset [68], which is used to predict psychological states. 4. **Cleveland** dataset, a dataset used to detect heart disease and used in various papers [69; 70]. 5. **Dermatology** dataset [71], which is used for differential diagnosis of erythematosquamous diseases. 6. **Glass** dataset. This dataset contains glass component analysis for glass pieces that belong to six classes. 7. **Hayes Roth** dataset [72]. This dataset contains **5** numeric-valued attributes and 132 patterns. 8. **Heart** dataset [73], used to detect heart disease. 9. **HouseVotes** dataset [74], which is about votes in the U.S. House of Representatives Congressmen. 10. **Liverdisorder** dataset [75], used to detect liver disorders in peoples using blood analysis. 11. **Ionosphere** dataset, a meteorological dataset used in various research papers [76; 77]. 12. **Mammographic** dataset [78]. This dataset can be used to identify the severity (benign or malignant) of a mammographic mass lesion from BI-RADS attributes and the patient's age. It contains 830 patterns of 5 features each. 13. **PageBlocks** dataset. The dataset contains blocks of the page layout of a document that has been detected by a segmentation process. It has 5473 patterns with 10 features each. 14. **Parkinsons** dataset, ref. [79], which is created using a range of biomedical voice measurements from 31 people, 23 with Parkinson's disease (PD). The dataset has 22 features. 15. **Pima** dataset [80], used to detect the presence of diabetes. 16. **PopFailures** dataset [81], used in meteorology. 17. **Regions2** dataset. It is created from liver biopsy images of patients with hepatitis C [82]. From each region in the acquired images, 18 shape-based and color-based features were extracted, while it was also annotated from medical experts. The resulting dataset includes 600 samples belonging to 6 classes. 18. **Saheart** dataset [83], used to detect heart disease. 19. **Segment** dataset [84]. This database contains patterns from a database of seven outdoor images (classes). 20. **Sonar** dataset [85]. The task here is to discriminate between sonar signals bounced off a metal cylinder and those bounced off a roughly cylindrical rock. 21. **Spiral** dataset, which is an artificial dataset with two classes. The features in the first class are constructed as: \(x_{1}=0.5t\cos(0.08t)\), \(x_{2}=0.5t\cos(0.08t+\frac{\pi}{2})\) and for the second class the used equations are : \(x_{1}=0.5t\cos(0.08t+\pi)\), \(x_{2}=0.5t\cos(0.08t+\frac{3\pi}{2})\). 22. **Wine** dataset, which is related to chemical analysis of wines [86; 87]. 23. **Wolbe** dataset [88], which contains data for breast tumors. 24. **EEG** dataset. As a real-world example, an EEG dataset described in [89; 90] is used here. The dataset consists of five sets (denoted as Z, O, N, F, and S), each containing 100 single-channel EEG segments and each having a 23.6 sec duration. Sets Z and O have been taken from surface EEG recordings of five healthy volunteers with eye open and closed, respectively.