ee.Image(image.updateMask(mask)).divide(10000).addBands(qa, null, true)
                .copyProperties(image).set("system:time_start", image.get("system:time_start"));

// bands to use the classification for
var bands = S2.first().bandNames().slice(1,12);
// Think about which image you want to use as input for the classifier:
// Do you have one 'perfect' image? Or do you want to classify based on every single image?

// map over the image collection, do the classification per-image
var classified = S2.map(function(image){
  var training = image.select(bands).sampleRegions({ collection: newfc, properties: ['id'], scale: 30 }); // print(training)
  var classifier = ee.Classifier.cart().train({ features: training, classProperty: 'id'});
  var classImage = image.select(bands).classify(classifier).rename('classified');
  return image.addBands(classImage);
});