James Thornton espeed

## gist:63fabb2e90009e7824d6b68b4cf876ad
https://www.youtube.com/watch?v=5mcPOd28oN0#D9fpFW_uXjA ZGCjx20hMbE LY6Rp9OdoO0

https://www.youtube.com/watch?v=Z-Z0jkeoAkA

## gist:dd3026536ec3d38afea1072941670f52
691136 705691 704201 710345 710477 702539 719740 733465 730899 735195 724022 736272

## gist:17b0744293b3eef2f6cbcb427450506a
### Keybase proof

I hereby claim:

  * I am espeed on github.
  * I am espeed (https://keybase.io/espeed) on keybase.
  * I have a public key whose fingerprint is 626C 87CB 743D 0402 F487  91A8 5BC5 5A31 5C09 DCA1

To claim this, I am signing this object:

## gist:bdd947cb5e922aaa3451c3c14cb73bf8
1

## file
{"0.8782798733075599":"-----BEGIN PGP PUBLIC KEY BLOCK-----\r\nCharset: UTF-8\r\n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\r\nW4Uyq2H+b1+iBriO9LDIs1pS2CGKGEKDPg==\r\n=qJ/3\r\n-----END PGP PUBLIC KEY BLOCK-----\r\n"}

## onename-jamesthornton.txt
Verifying that +jamesthornton is my blockchain ID. https://onename.com/jamesthornton

## Onename espeed
Verifying that +espeed is my blockchain ID. https://onename.com/espeed

## output
python ./nltk-trainer/train_classifier.py ./data/googleNews --instances files --fraction 0.75 --min_score 2 --ngrams 1 2 3 --show-most-informative 10 --classifier NaiveBayes
loading ./data/googleNews
2 labels: ['neg', 'pos']
calculating word scores
using bag of words from known set feature extraction
1682507 words meet min_score and/or max_feats
37116 training feats, 12371 testing feats
training NaiveBayes classifier
accuracy: 0.582815
neg precision: 0.659028

## nltk-trainer-ngram-classifier-example-timed.py
import timeit
import pickle
import nltk.data
from nltk.util import ngrams

t0 = timeit.default_timer()

## nltk-trainer-sklearn.MultinomialNB.py
$ python
Python 2.7.10 (default, Jul  5 2015, 14:15:43)
[GCC 5.1.1 20150618 (Red Hat 5.1.1-4)] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> import scipy
>>> scipy.__version__
'0.14.1'
>>> import numpy
>>> numpy.__version__
'1.9.2'
	https://www.youtube.com/watch?v=5mcPOd28oN0#D9fpFW_uXjA ZGCjx20hMbE LY6Rp9OdoO0

	https://www.youtube.com/watch?v=Z-Z0jkeoAkA
	### Keybase proof

	I hereby claim:

	* I am espeed on github.
	* I am espeed (https://keybase.io/espeed) on keybase.
	* I have a public key whose fingerprint is 626C 87CB 743D 0402 F487 91A8 5BC5 5A31 5C09 DCA1

	To claim this, I am signing this object:
	python ./nltk-trainer/train_classifier.py ./data/googleNews --instances files --fraction 0.75 --min_score 2 --ngrams 1 2 3 --show-most-informative 10 --classifier NaiveBayes
	loading ./data/googleNews
	2 labels: ['neg', 'pos']
	calculating word scores
	using bag of words from known set feature extraction
	1682507 words meet min_score and/or max_feats
	37116 training feats, 12371 testing feats
	training NaiveBayes classifier
	accuracy: 0.582815
	neg precision: 0.659028
	import timeit
	import pickle
	import nltk.data
	from nltk.util import ngrams

	t0 = timeit.default_timer()
	$ python
	Python 2.7.10 (default, Jul 5 2015, 14:15:43)
	[GCC 5.1.1 20150618 (Red Hat 5.1.1-4)] on linux2
	Type "help", "copyright", "credits" or "license" for more information.
	>>> import scipy
	>>> scipy.__version__
	'0.14.1'
	>>> import numpy
	>>> numpy.__version__
	'1.9.2'