| ANOVA_SUMMARY = function(formula, data) | |
| { | |
| # 1. 데이터 전처리 | |
| # 종속변수를 항상 첫번째 input으로 "y~." 형식으로 받음 | |
| mf = model.frame(formula, data) | |
| y = mf[,1] | |
| Response_name = colnames(mf)[1] # 종속변수의 이름 | |
| Variable_name = c("(intercept)", colnames(mf)[-1]) # 독립변수의 이름 | |
| n = nrow(mf) |
| """ Trains an agent with (stochastic) Policy Gradients on Pong. Uses OpenAI Gym. """ | |
| import numpy as np | |
| import cPickle as pickle | |
| import gym | |
| # hyperparameters | |
| H = 200 # number of hidden layer neurons | |
| batch_size = 10 # every how many episodes to do a param update? | |
| learning_rate = 1e-4 | |
| gamma = 0.99 # discount factor for reward |
| ; 새 생명. | |
| (NP (DP 새/MM) | |
| (NP 생명/NNG + ./SF)) | |
| ; 나는 돈이다. | |
| (S (NP_SBJ 나/NP + 는/JX) | |
| (VNP 돈/NNG + 이/VCP + 다/EF + ./SF)) | |
| ; 만 원이라는 이름을 붙인 채, 이제 막 태어났다. | |
| (VP (NP_AJT (VP_MOD (NP_OBJ (VNP_MOD (NP 만/NR) |
| # Reference: http://konlpy.org/en/v0.4.4/install/#ubuntu | |
| sudo apt-get update && sudo apt-get upgrade | |
| sudo apt-get install g++ openjdk-7-jdk python-dev python3-dev --fix-missing | |
| sudo pip install JPype1 | |
| sudo pip install konlpy | |
| sudo apt-get install curl | |
| bash <(curl -s https://raw.githubusercontent.com/konlpy/konlpy/master/scripts/mecab.sh) |
| from konlpy.tag import Mecab | |
| mecab = Mecab() | |
| import sys | |
| reload(sys) | |
| sys.setdefaultencoding('utf-8') | |
| def mecab_pos_tag(): | |
| while True: | |
| a = raw_input() | |
| for x in mecab.pos(a): |
With NLTK version 3.1 and Stanford NER tool 2015-12-09, it is possible to hack the StanfordNERTagger._stanford_jar to include other .jar files that are necessary for the new tagger.
First set up the environment variables as per instructed at https://github.com/nltk/nltk/wiki/Installing-Third-Party-Software
| sudo apt-get upgrade | |
| sudo apt-get update | |
| sudo pip install jupyter notebook | |
| jupyter notebook --generate-config | |
| ipython | |
| from notebook.auth import passwd | |
| passwd() |
| # Note – this is not a bash script (some of the steps require reboot) | |
| # I named it .sh just so Github does correct syntax highlighting. | |
| # | |
| # This is also available as an AMI in us-east-1 (virginia): ami-cf5028a5 | |
| # | |
| # The CUDA part is mostly based on this excellent blog post: | |
| # http://tleyden.github.io/blog/2014/10/25/cuda-6-dot-5-on-aws-gpu-instance-running-ubuntu-14-dot-04/ | |
| # Install various packages | |
| sudo apt-get update |
| import csv | |
| import os | |
| def get_csv_writer(filename, rows, delimiter): | |
| with open(filename, 'w') as csvfile: | |
| fieldnames = rows[0].keys() | |
| writer = csv.DictWriter(csvfile, fieldnames=fieldnames, delimiter=delimiter) | |
| writer.writeheader() | |
| for row in rows: | |
| try: |
| from __future__ import absolute_import | |
| from __future__ import division | |
| from __future__ import print_function |