sklearn select N best using classifier
class_weight is used in the process of model-training to train(=fit) a better model (let us call it clf).

Your question is is about choosing the most sure predictions.
You just need to predict the probability (for binary classification this will be the probability of positive class)

y_test_predicted_probability = clf.predict_proba(X_test)


and then choose 10 points with the highest y_test_predicted_probability

#some code to do this
top_picks_indexes = y_test_predicted_probability[:,1].argsort()[-10:] # chose top 10 probabilities for class = 1

# create a vector, Y_top_picks, with all zeros except ones for the selected top probabilities
Y_top_picks = np.zeros(len(X_test))
Y_top_picks[top_picks_indexes] = 1