Yuu Ito yuu-ito

標本数の決め方について調べてみる。

主なものとして

共起尺度、共起頻度の指標は自然言語処理関連でよく使われているらしい。

logistic <- function(z) 1/(1 + exp(-z))

	<!DOCTYPE html>
	<html lang="ja">
	<head>
	<meta charset="UTF-8">
	<title></title>
	<script type="text/javascript" src="https://cdnjs.cloudflare.com/ajax/libs/vue/0.12.16/vue.min.js"></script>
	</head>
	<body>
	<h1>タイピングてすと：function</h1>
	function + enter で計測

	get_latlng_from_address<-function(zipcode){
	require("rjson")
	url.template<-"http://maps.googleapis.com/maps/api/geocode/json?language=ja&address"
	url <- paste(url.template,zipcode,sep="=")
	map_data <- fromJSON(paste(readLines(url), collapse=""))
	if(map_data$status=="OK"){
	address_info <- map_data$results[[1]]$address_components
	location <- map_data$results[[1]]$geometry$location
	res <- data.frame(
	zipcode= zipcode,

	# kaggle titanic
	# https://www.kaggle.com/c/titanic-gettingStarted/data


	t <- read.csv("../../Downloads/train.csv")
	names(t)<-tolower(names(t))

	idx<- sample(nrow(t),(nrow(t)*0.7))
	t.tr <- t[ idx,]
	t.te <- t[-idx,]

	# install.packages("party")
	library("party")
	# ?ctree
	irisct <- ctree(Species ~ .,data = iris)
	irisct
	plot(irisct)

	// Use Gists to store code you would like to remember later on
	console.log(window); // log the "window" object to the console