202 reputation
26
bio website
location
age
visits member for 2 years, 8 months
seen Jan 29 at 17:54
stats profile views 67

I'm just a cool boy


Apr
10
awarded  Yearling
Nov
25
awarded  Popular Question
May
29
awarded  Necromancer
Apr
28
revised Mean and median in Zipf's distribution
added 90 characters in body; added 2 characters in body
Apr
27
revised Mean and median in Zipf's distribution
added 6 characters in body
Apr
27
comment Mean and median in Zipf's distribution
I meant inverted index, that is for each for w I have a list of documents in which a particular word w occurs. inverted_index[w] = {doc1, doc2, doc6}. In a similar fashion as index of terms at the back of the book.
Apr
27
asked Mean and median in Zipf's distribution
Apr
3
accepted Inference with Gaussian Random Variable
Apr
3
revised Inference with Gaussian Random Variable
added 36 characters in body
Apr
2
comment Inference with Gaussian Random Variable
Thanks for a swift answer, not a homework though. Would have tagged it as such if it really was.
Apr
2
revised Inference with Gaussian Random Variable
edited body
Apr
2
revised Inference with Gaussian Random Variable
added 3 characters in body; added 2 characters in body
Apr
2
asked Inference with Gaussian Random Variable
Mar
8
accepted Efficient way to classify with SVM
Mar
8
comment Efficient way to classify with SVM
after applying weighted penalty for each class it works faster. Going through all the mathematical intricacies of SVM now. Thanks for help
Mar
5
comment Efficient way to classify with SVM
C-SVC, 26k 9-dimensional vectors, polynomial kernel. Just edited grid.py to maximize F-scores instead, but still looking for some clever options to run SVM Classfier.
Mar
5
revised Efficient way to classify with SVM
added 87 characters in body; edited title
Mar
5
revised Efficient way to classify with SVM
added 345 characters in body
Mar
5
comment Efficient way to classify with SVM
I have made an approach to maximize F-Score using grid search but it's very expensive, almost infeasible.
Mar
5
revised Efficient way to classify with SVM
added 1 characters in body