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library(ggplot2)

# returns the odds of a model given an input vector x
get_log_odds <- function(model,x) {
  n_coeff <- length(model$coefficients)
  
  if (n_coeff - length(x) == 1) {
    # user forgot the first 1 in [1, x1,...]
    x <- c(1,x)

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source('helpers.R')


# ========================================
# ==============[ Q 3.3.1 ]===============
# ========================================

load('hilda.Rdata')

# redefine the hospitaldays to be 1 for anything above 1

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# ========================================
# ==============[ Q 3.2.1 ]===============
# ========================================
load('hilda.Rdata')
source('helpers.R')

hilda <- setup_data_base(hilda)

# form the first model by splitting the ages into groups of five

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# ========================================
# ==============[ Q 3.1.1 ]===============
# ========================================

# load data
load('hilda.Rdata')
source('helpers.R')

# redifine the hospitaldays to be 1 for anything above 1
hilda$hospdays[(hilda$hospdays >= 1)] = 1

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library(ggplot2)
source('helpers.R')



# ======================================
# ==============[ Q 3.4 ]===============
# ======================================

# prepare the model by defining factors

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library(ggplot2)
source('helpers.R')

load('data.Rda')
head(data)

####### Setup data

data$crm <- (data$crimes / data$popul) * 1000
data$crm <- ceiling(data$crm)

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using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using DataReader.Extensions;
using iTextSharp.text.log;
using iTextSharp.text.pdf;
using iTextSharp.text.pdf.parser;

namespace DataReader.ExploredCode

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Using decorators in React Native

1. Install babel plugins to enable decorators.

   npm install babel-plugin-transform-decorators-legacy --save-dev

2. Create or update your .babelrc file in root folder:

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d

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# Example Dockerfile
FROM hello-world