zhicongchen

def smart_procrustes_align_gensim(base_embed, other_embed, words=None):
    """
    Original script: https://gist.github.com/quadrismegistus/09a93e219a6ffc4f216fb85235535faf
    Procrustes align two gensim word2vec models (to allow for comparison between same word across models).
    Code ported from HistWords <https://github.com/williamleif/histwords> by William Hamilton <wleif@stanford.edu>.
        
    First, intersect the vocabularies (see `intersection_align_gensim` documentation).
    Then do the alignment on the other_embed model.
    Replace the other_embed model's syn0 and syn0norm numpy matrices with the aligned version.
    Return other_embed.

louridas

import numpy as np
import gensim

def smart_procrustes_align_gensim(base_embed, other_embed, words=None):
    """Procrustes align two gensim word2vec models (to allow for comparison between same word across models).
    Code ported from HistWords <https://github.com/williamleif/histwords> by William Hamilton <wleif@stanford.edu>.
    (With help from William. Thank you!)
    First, intersect the vocabularies (see `intersection_align_gensim` documentation).
    Then do the alignment on the other_embed model.
    Replace the other_embed model's syn0 and syn0norm numpy matrices with the aligned version.

dmasad

chengjun

library(plyr)
library(ggplot2)
library(grid)


election.data <- read.csv("http://www.oberlin.edu/faculty/cdesante/assets/downloads/election2012.csv")
five.thirty.free <- function (SIMS) {

  Mode <- function(X) {

stevenworthington

# ipak function: install and load multiple R packages.
# check to see if packages are installed. Install them if they are not, then load them into the R session.

ipak <- function(pkg){
    new.pkg <- pkg[!(pkg %in% installed.packages()[, "Package"])]
    if (length(new.pkg)) 
        install.packages(new.pkg, dependencies = TRUE)
    sapply(pkg, require, character.only = TRUE)
}

halpo

Building a beamer presentation with knitr.

Introduction

The documents included are the input for knitr. In addition you need to have the tool pandoc installed. I also use a custom beamer template to add the University of Utah \institute command to the template. It also changes the indentation some.

Steps

1. knit document with

xccds

# 导入数据
text <- readLines('d:\\honglou.txt',encoding='UTF-8')

library(ggplot2)
library(rmmseg4j)
library(tm)
library(MASS)
library(proxy)

#去除空白行

chengjun

`r opts_chunk$set(cache=TRUE)`

This is a quick set of analyses of the California Test Score dataset.  The post was produced using R Markdown in RStudio 0.96.  The main purpose of this post is to provide a case study of using R Markdown to prepare a quick reproducible report.  It provides examples of using plots, output, in-line R code, and markdown. The post is designed to be read along side the R Markdown source code, which is available as a gist on github. 

<!-- more -->

### Preliminaries
* This post builds on my earlier post which provided a guide for [Getting Started with R Markdown, knitr, and RStudio 0.96](jeromyanglim.blogspot.com/2012/05/getting-started-with-r-markdown-knitr.html)
* The dataset analysed comes from the `AER` package which is an accompaniment to the book [Applied Econometrics with R](http://www.amazon.com/Applied-Econometrics-R-Use/dp/0387773169) written by [Christian Kleiber](http://wwz.unibas.ch/personen/profil/person/kleiber/) and [Achim Zeileis](http://eeecon.uibk.ac.at/~zeileis/

alstat

library(ggplot2)
library(colorRamps)

TawiTawiPop <- c(17000, 45000, 46000, 59000, 79000, 110000, 143000, 195000, 228204,
                 250718, 322317, 450346, 366550)
YearNames <- c("1903", "1918", "1939", "1948", "1960", "1970", "1975", "1980", "1990",
               "1995", "2000", "2007", "2010")

qplot(YearNames, TawiTawiPop, 
      xlab = expression(bold("Censal Year")), 

theconektd

body {
  font-family: Helvetica, arial, sans-serif;
  font-size: 14px;
  line-height: 1.6;
  padding-top: 10px;
  padding-bottom: 10px;
  background-color: white;
  padding: 30px; }

body > *:first-child {