Return best n categories when predicting #60
Description
Is your feature request related to a problem? Please describe.
In my case (using PLDA for information retrieval) it'd better to predict [let's say] best n options instead of the best one for a given query.
I figured out that the predict method does not support this feature. But it can be done using calc_logp_pp_categories method.
Describe the solution you'd like
My fast solution for solving this was to use bellow code:
def predict_doc_at(query, k=1):
"""
Predict which document is matched to the given query.
:param query: input query
:type query: str (or list of strs)
:param k: number of returning docs
:type k: int
:return: return the document name
"""
query_embedding = get_embeddings(query)
data = PLDA_classifier.model.transform(query_embedding,
from_space='D',
to_space='U_model')
logpps_k, K = PLDA_classifier.calc_logp_pp_categories(data,
False)
best_k_idx = logpps_k.argsort()[::-1][:k]
predictions = K[best_k_idx]
return accuracy, predictions