diff --git a/README.md b/README.md index 1eba657f538b7995e169fcb8000f684d6e777153..9c78eb8bae56f1ccc5df38c5eef5d8b446bc11a0 100644 --- a/README.md +++ b/README.md @@ -4,19 +4,19 @@ This repository contains the first draft of the programming part for the master ## Installation -To interpret the included Python code, the OGB library is required. Follow the instructions on the official homepage: +To interpret the included Python code, the OGB library is required. Follow the instructions on the official homepage:<br /> https://ogb.stanford.edu/docs/home/ -To follow the complete process libFM is necessary. The software can be easily cloned from the following repository: +To follow the complete process libFM is necessary. The software can be easily cloned from the following repository:<br /> https://github.com/srendle/libfm Use the following folder structure: - ├──MasterThesisProposal + ├── MasterThesisProposal │ ├── libfm │ │ ├── libfm.exe - │ │ ├── Generated data files - │ │ ├── Prediction file (after execution) + │ │ ├── Generated data files (move here after python execution) + │ │ ├── Prediction file (after libfm execution) │ ├── Python │ │ ├── DataPrePro & Evaluation @@ -25,7 +25,7 @@ Use the following folder structure: Start the downloaded Python file and follow the instructions. The first time you run it, the dataset is downloaded and a folder is created for it. After creating the data files you have to run libFM. To do this, copy your generated data into the libFM folder. A more detailed description of how to start the program and how it works can be found in the ReadMe of the libFM repository. The program will then generate a prediction file based on your files. After this file appears in the libFM folder you can run the Python file and look at the evaluation metrics. -> At the moment the number of examples are limited. If you want to change the value, do it in the following line: +>At the moment the number of examples are limited. If you want to change the value, do it in the following line: ```python if index >= 200000: break