Category "precision-recall"

ValueError: Shapes (None, 1) and (None, 5) are incompatible in keras

model = Sequential() model.add(Conv2D(128, (3, 3), activation='relu', input_shape=(64, 64, 3), padding='same')) model.add(MaxPooling2D(pool_size=(2, 2))) mode

ValueError: Shapes (None, 1) and (None, 5) are incompatible in keras

model = Sequential() model.add(Conv2D(128, (3, 3), activation='relu', input_shape=(64, 64, 3), padding='same')) model.add(MaxPooling2D(pool_size=(2, 2))) mode

FastText 0.9.2 - why is recall 'nan'?

I trained a supervised model in FastText using the Python interface and I'm getting weird results for precision and recall. First, I trained a model: model = fa

Using precision recall metric on a hierarchy of recovered clusters

Context: We are two students intending to write a thesis on reverse engineering namespaces using hierarchical agglomerative clustering algorithms. We have a var