adamcone

predict_function_full = function(test.obs){
  obs.NAs = sum(is.na(test.obs))
  
  if(obs.NAs == 0){
    return(predict(M0.svm.full, test.obs[-1], probability = TRUE, na.rm = TRUE))
  }
  else if(obs.NAs == 1){
    return(predict(M1.svm.full, test.obs[-1], probability = TRUE, na.rm = TRUE))
  }
  else if(obs.NAs == 7){

adamcone

cost = seq(-3, 5, length = 3)
gamma = seq(-5, 1, length = 3)

set.seed(0)
M0.index = sample(1:nrow(M0.training), 10000)
cv.svm.M0 = tune(svm,
                Label ~ .,
                data = M0.training[M0.index, -c(1, ncol(M0.training) - 1)],
                kernel = "radial",
                ranges = list(cost = 10^(cost), 

adamcone

library("shiny")
library("dplyr")
library("ggplot2")

# I will create a function that inputs the parameters the user is prompted for,
# and main data frame items_tbl, and outputs a data frame that will be used for
# plotting the histogram.

items_filter = function(items_tbl,
                        Price_Range_selected,

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library(shiny)
library(dplyr)
library(ggplot2)
source("./helpers.R")
load("./shinydataframe.RData")

server <- function(input, output) {
  data <- eventReactive(input$go, {items_filter(items_tbl,
                                                input$Price_Range_selected,
                                                input$Payment_Types_selected,

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library(shiny)
library(dplyr)


fluidPage(
  titlePanel("What Kind of Revenue Interests You?"),
  sidebarLayout(
    sidebarPanel(
      sliderInput(inputId = "Price_Range_selected",
                  label = h3("Product Unit Price Range ($)"),

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# preparing data for Shiny app

load("/Users/adamcone/Desktop/projects/Shiny Project/data munging/op_data_conversion_filtered.RData")
rm(sales_tbl)
items_tbl = select(items_tbl, DateTime, Payment_Type, Unit_Cost, Item_Total)
items_tbl = mutate(items_tbl, Date = as.Date(DateTime))

first_date = as.Date(min(items_tbl$DateTime))
last_date = as.Date(max(items_tbl$DateTime))
break_points = seq(from = first_date,