Update README.md

Adjust participation

README.md

@@ -26,11 +26,15 @@ During this challenge phase, the Liss dataset is used, which is split into a tra
 
 ### Participation [Work in progress]
 
-1. Fork and clone [this](https://github.com/eyra/fertility-prediction-challenge) repository as explained [here](https://github.com/eyra/fertility-prediction-challenge/wiki#how-to-fork-and-clone-this-repository).
-2. Change the content of the **predict_outcomes function** in [submission.py](https://github.com/eyra/fertility-prediction-challenge/blob/master/src/submission.py) as explained in the script to include your method. Do not change the expected input and output data format.
-3. The metrics used to create the challenge [leaderboards](https://github.com/eyra/fertility-prediction-challenge/tree/master#leaderboard) are included in this repo. You can separate the challenge example data into a train and test set and use the score function in [submission.py](https://github.com/eyra/fertility-prediction-challenge/blob/master/src/submission.py) to determine your method performance scores on the example data as described [here](https://github.com/eyra/fertility-prediction-challenge/wiki#how-to-evaluate-your-method).
-4. Submit your method as explained [here](https://github.com/eyra/fertility-prediction-challenge/tree/master#how-to-submit-your-method).
-5. Your performance scores on the challenge [leaderboards](https://github.com/eyra/fertility-prediction-challenge/tree/master#leaderboard) will become available after signing in on the Next platform ([Round 1](https://eyra.co/benchmark/5), [Round 2](https://eyra.co/benchmark/6)).
+1. After you have forked and cloned this repository (see preparation), you can start adding your method.
+2. Go to submission.py or submission.R depending on your preferred programming language. These files contain example scripts.
+3. Develop your prediction method (i.e. train your model). To participate in the challenge you need to adjust the submission script to include your method. This is the script that will be run on the holdout data after submission.
+4. Add data cleaning (preprocessing) to clean_df(df) 
+
+Change the content of the **predict_outcomes function** in [submission.py](https://github.com/eyra/fertility-prediction-challenge/blob/master/src/submission.py) as explained in the script to include your method. Do not change the expected input and output data format.
+6. The metrics used to create the challenge [leaderboards](https://github.com/eyra/fertility-prediction-challenge/tree/master#leaderboard) are included in this repo. You can separate the challenge example data into a train and test set and use the score function in [submission.py](https://github.com/eyra/fertility-prediction-challenge/blob/master/src/submission.py) to determine your method performance scores on the example data as described [here](https://github.com/eyra/fertility-prediction-challenge/wiki#how-to-evaluate-your-method).
+7. Submit your method as explained [here](https://github.com/eyra/fertility-prediction-challenge/tree/master#how-to-submit-your-method).
+8. Your performance scores on the challenge [leaderboards](https://github.com/eyra/fertility-prediction-challenge/tree/master#leaderboard) will become available after signing in on the Next platform ([Round 1](https://eyra.co/benchmark/5), [Round 2](https://eyra.co/benchmark/6)).
 
 ℹ️ It takes some time to process the results for the leaderboards.