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Bachelor-Thesis

Code and files of the practical work of my thesis

Project Organization

├── README.md          <- The top-level README for developers using this project
├── data
│   ├── processed      <- Contains the pre-processed datasets ready for feature extracting
│   └── raw            <- Contains the original datasets (records.bib is converted to WagnerPrester_2023.csv)
│
├── notebooks     
│   ├── bib-csv-converter.ipynb						<- bib to csv converter for WagnerPrester_2023 dataset
│   ├── Complete Comparison.ipynb					<- Complete implementation to receive results for all combinations of Datasets&Feature Extractor&Classifier
│	└── Feature Extractor&Classifier&Dataset Averager.ipynb         <- Averages the results for every Datasets&Feature Extractor&Classifier and sorts the results by dataset and recall       
│
├── references        
│	└── Datasets sources.txt 	<- Contains the references of the used datasets 
│
├── reports            
│ 	├── average_classifier.txt      		<- Average performance results for the classifiers sorted by recall
│	├── average_combination.txt     		<- Average performance results for the combinations of feature extractor&classifier sorted by recall
│	├── average_datasets.txt      			<- Average performance results for the datasets sorted by recall
│	├── average_feature_extractor.txt      		<- Average performance results for the feature extractor sorted by recall
│	├── full_results.csv      			<- Results for all combinations of Datasets&Feature Extractor&Classifier as csv file
│	├── full_results      				<- Results for all combinations of Datasets&Feature Extractor&Classifier as txt file
│	└── full_results_sortedByDataset&Recall      	<- Results for all combinations of Datasets&Feature Extractor&Classifier sorted by datasets and recall

Project based on the cookiecutter data science project template. #cookiecutterdatascience

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