I'm building a chain classifier for a multiclass problem that uses Keras binary Classifier model in a chain. I have 17 labels as classification target and datas
I am working on an image classification task to classify among cars and buses. The problem is that in most car images, there is buses in the background and vice
I am trying to solve one multilabel problem with 270 labels and i have converted target labels into one hot encoded form. I am using BCEWithLogitsLoss(). Since
Can someone please explain (with example maybe) what is the difference between OneVsRestClassifier and MultiOutputClassifier in scikit-learn? I've read docume
I'm a beginner to this field and am stuck. I am following this tutorial (https://towardsdatascience.com/multi-label-multi-class-text-classification-with-bert-tr