Error in supervised classification output (Earth Engine)

Question

I have a problem in the supervised classification output. The classification itself is giving any problem, but when I try to print or display the image I obtain this error:

Image (Error) Unable to use a collection in an algorithm that requires a feature or image. This may happen when trying to use a collection of collections where a collection of features is expected; use flatten, or map a function to convert inner collections to features. Use clipToCollection (instead of clip) to clip an image to a collection.

Here is the code: https://code.earthengine.google.com/9dae0afc574251bd102e81e10850dd82

I'm pretty sure that the problem is from line 103 to 128. Here I created a polygon from a raster, and set it as a FeatureCollection in order to set a class WATER with value = 1. If I use polygons created by giving the coordinates of nodes, I don't have this problem in the classification. I'll attach another link where I use polygons and don't have any problem: https://code.earthengine.google.com/6b03174ebd1c75a9281944c4a17c78b3

The problem is that I need to use the polygon from the raster and I have no clue how to solve this problem.

Answer 1

I am not 100 % sure if I have solved the complete issue as the resulting classification still seems weird to me but at least I managed to get rid of the error message.

I think the issue was with the variable trainingSet. When I printed it, it was a featurecollection of: (1) a very weird looking MultiPolygon with many self-intersects and (2) a feature collection spread over the entire ROI.

Sampling the regions does not seem to work with this weird list of a Multipolygon and Feature collection but when I extract the second feature collection and only sample these regions, the code is working.

I hope this helps!

// creation of the training set
var trainingSet = classW.merge(classNoW);

trainingSet = trainingSet.toList(2);
var weirdPols = ee.Feature(trainingSet.get(1));
Map.addLayer(weirdPols, null, 'Weird Polygons');
trainingSet = ee.FeatureCollection(trainingSet.get(1));
Map.addLayer(trainingSet, null, 'TrainingSet');