Jaemin Cho j-min

## Mecab-ko_iter.py
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):

## KoNLPy Install (Ubuntu & Python 2)
# 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)

## sejong_treebank.txt.v1
; 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)

## RNN_hunkim's_tutorial_BasicRNNCell.ipynb

      
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                j-min
                / RNN_hunkim's_tutorial_BasicRNNCell.ipynb
            
            
              Last active
              December 11, 2018 02:06
            
              
                TensorFlow 0.9 implementation of BasicRNNCell based on hunkim's tutorial
              
          
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## pg-pong.py
""" 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

## .vimrc
set nocompatible              " required
" filetype off                  " required
syntax on
syntax enable

" Monokai color scheme
" mkdir -p ~/.vim/colors
" wget https://raw.githubusercontent.com/crusoexia/vim-monokai/master/colors/monokai.vim ~/.vim/colors
colorscheme monokai

## R_custom_ANOVA&Summary
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)
	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):
	# 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)
	; 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)
	""" 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
	set nocompatible " required
	" filetype off " required
	syntax on
	syntax enable

	" Monokai color scheme
	" mkdir -p ~/.vim/colors
	" wget https://raw.githubusercontent.com/crusoexia/vim-monokai/master/colors/monokai.vim ~/.vim/colors
	colorscheme monokai
	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)