Added notes from 1st meeting

README.md

 # ML Project - Operator Decision
+
+## 1st Meeting
+TODO:
+
+- Read data
+- Read report from student
+- Reproduce the MLP model on our own
+- Check the statistical model (methods used for the first classification) -> see paper 
+- Check other paper for methods for false alarm detection (See project proposal)
+
+Additional notes:
+- we use features calculated from data rather than fill data with 0 when we have different resolutions (better performance) 
+    - option for later: add own features
+- database: only alarms -> classified as good/bad
+- data unit: the full profile -> reject/accept the whole profile as bad/good
+- use Pytorch
+- Meeting One day/week -> 16h friday 12.04
+- problem with database : not large
+	- careful by splitting -> require class balance (reduces number of data used)
+	- depending on splitting -> different performance
+	- solutions: replicate database, class balance (but for now just implement it like this)
+- historical data -> from boyes; what about the other datasets ? 
+- in-situ -> field study