Update README.md

README.md

@@ -72,15 +72,10 @@ The following leaderboards will be available:
 - [Recall](https://developers.google.com/machine-learning/crash-course/classification/precision-and-recall)\*
 - Overall [accuracy](https://developers.google.com/machine-learning/crash-course/classification/accuracy)
 
-\*_For the prediction of having a child in 2020-2022 (positive class)_.
+\*_For the prediction of having a child in 2021-2023 (positive class)_.
 
 For this challenge the F1 leaderboard is the main leaderboard.
 
-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(prediction_path, ground_truth_path, output)``` function in [run.py](https://github.com/eyra/fertility-prediction-challenge/blob/master/run.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)).
-
 ## License
 
 This project is licensed under the terms of the [MIT license](https://github.com/eyra/fertility-prediction-challenge/blob/master/LICENSE).