Firsly thank you for this awesome work.
There is something that I'm not sure to understand :
t1,_1 = awesome_cossim_topn(X, Y.T, 1,0.5,return_best_ntop=True)
t2,_2 = awesome_cossim_topn(X, Y.T, 10,0.5,return_best_ntop=True)
This two lines return me the same things. It looks like the value N doesn't matter and also the arguement return_best_ntop.
X and Y are as follow :
vec1 = TfidfVectorizer(lowercase=False, analyzer="char", ngram_range=(2, 3))
vec = vec1.fit(vendor_names + spend_vendor_name)
X = vec1.transform(vendor_names)
Y = vec1.transform([spend_vendor_name])
with vendor_name = List[str] of length 2 millions and spend_vendor_name = "goldman sach aim".
Hello,
Firsly thank you for this awesome work. There is something that I'm not sure to understand : t1,_1 = awesome_cossim_topn(X, Y.T, 1,0.5,return_best_ntop=True) t2,_2 = awesome_cossim_topn(X, Y.T, 10,0.5,return_best_ntop=True)
This two lines return me the same things. It looks like the value N doesn't matter and also the arguement return_best_ntop.
X and Y are as follow : vec1 = TfidfVectorizer(lowercase=False, analyzer="char", ngram_range=(2, 3)) vec = vec1.fit(vendor_names + spend_vendor_name)
X = vec1.transform(vendor_names) Y = vec1.transform([spend_vendor_name])
with vendor_name = List[str] of length 2 millions and spend_vendor_name = "goldman sach aim".
Thank you