People
 :bowtie: |
😄 :smile: |
😆 :laughing: |
|---|---|---|
😊 :blush: |
😃 :smiley: |
:relaxed: |
😏 :smirk: |
😍 :heart_eyes: |
😘 :kissing_heart: |
😚 :kissing_closed_eyes: |
😳 :flushed: |
😌 :relieved: |
😆 :satisfied: |
😁 :grin: |
😉 :wink: |
😜 :stuck_out_tongue_winking_eye: |
😝 :stuck_out_tongue_closed_eyes: |
😀 :grinning: |
😗 :kissing: |
😙 :kissing_smiling_eyes: |
😛 :stuck_out_tongue: |
| from sklearn.metrics import confusion_matrix | |
| def print_cm(cm, labels, hide_zeroes=False, hide_diagonal=False, hide_threshold=None): | |
| """pretty print for confusion matrixes""" | |
| columnwidth = max([len(x) for x in labels]+[5]) # 5 is value length | |
| empty_cell = " " * columnwidth | |
| # Print header | |
| print " " + empty_cell, | |
| for label in labels: | |
| print "%{0}s".format(columnwidth) % label, |
| # -*- coding: utf-8 -*- | |
| from __future__ import unicode_literals | |
| from nltk.tokenize import RegexpTokenizer | |
| import argparse | |
| import os | |
| """ | |
| Script for tokenizing Portuguese text according to the Universal Dependencies | |
| (UD) tokenization standards. This script was not created by the UD team; it was |
DBpedia SPARQL Explorer: http://dbpedia.org/snorql/
DBpedia Virtuoso SPARQL Query Editor: https://dbpedia.org/sparql
=====
People and death-causes
PREFIX dbo: <http://dbpedia.org/ontology/>
