# 50% accuracy on multiclass classification

I am trying to do a multiclass classification on a significant amount of output labels (1000).

I built a model using KNN. The accuracy given by accuracy = knn.score(X_test, y_test) is 0.5.

Does this mean that given an input, the model is able to predict 50% of the time which label the data belongs to? If yes, I would intuitively say that this is good, since randomly choosing a label would have a probability of 0.1%.

• What is the class distribution of your data and predictions? – Sammy Feb 26 '20 at 8:57