Nothing
## ----results = "asis", message = FALSE, warning = FALSE, eval = FALSE---------
# library(datarobot)
## ----results = "asis", message = FALSE, warning = FALSE, eval = FALSE---------
# ConnectToDataRobot(endpoint = "YOUR-ENDPOINT-HERE", token = "YOUR-API_TOKEN-HERE")
## ---- echo = FALSE, message = FALSE-------------------------------------------
library(AmesHousing)
Ames <- make_ames()
Ames <- Ames[sapply(Ames,is.numeric)]
## ---- echo = TRUE, message = FALSE--------------------------------------------
head(Ames)
## ---- echo = TRUE, eval = FALSE-----------------------------------------------
# project <- StartProject(dataSource = Ames,
# projectName = "AmesVignetteProject",
# target = "Sale_Price",
# wait = TRUE)
## ---- echo = FALSE------------------------------------------------------------
project <- readRDS("AmesprojectObject.rds")
project
## ----echo=FALSE, message=FALSE, warning=FALSE---------------------------------
library(datarobot)
listOfAmesModels <- readRDS("listOfAmesModels.rds")
fullFrame <- as.data.frame(listOfAmesModels, simple = FALSE)
## ---- echo = TRUE, eval = FALSE-----------------------------------------------
# listOfAmesModels <- ListModels(project)
## ---- echo = TRUE-------------------------------------------------------------
summary(listOfAmesModels)
## ---- echo = TRUE, fig.width = 7, fig.height = 6, fig.cap = "Horizontal barplot of modelType and validation set Gamma Deviance values for all project models"----
plot(listOfAmesModels, orderDecreasing = TRUE)
## ---- echo = TRUE-------------------------------------------------------------
modelFrame <- as.data.frame(listOfAmesModels)
head(modelFrame[, c("modelType", "validationMetric")])
## ---- echo = TRUE-------------------------------------------------------------
tail(modelFrame[, c("modelType", "validationMetric")])
## ---- echo = TRUE-------------------------------------------------------------
Filter(function(m) grepl("Elastic-Net", m), modelFrame$expandedModel)
## ---- echo = TRUE, eval = FALSE-----------------------------------------------
# bestModel <- GetRecommendedModel(project,
# type = RecommendedModelType$RecommendedForDeployment)
# bestPredictions <- Predict(bestModel, Ames)
## ---- echo = TRUE, eval = FALSE-----------------------------------------------
# bestModel$modelType
## ---- echo = FALSE, eval = TRUE-----------------------------------------------
"eXtreme Gradient Boosted Trees Regressor (Gamma Loss)"
## ---- echo = FALSE, fig.width = 7, fig.height = 6-----------------------------
Sale_Price <- Ames$Sale_Price
bestPredictions <- readRDS("bestPredictionsAmes.rds")
plot(Sale_Price, bestPredictions, xlab="Observed Sale Price", ylab="Predicted Sale Price value",
ylim = c(0, 800000))
abline(a = 0, b = 1, lty = 2, lwd = 3, col = "red")
title("Best model")
## ---- echo = TRUE, eval = FALSE-----------------------------------------------
# impact <- GetFeatureImpact(bestModel)
# head(impact)
## ---- echo = FALSE------------------------------------------------------------
impact <- readRDS("IntroFeatureImpactAmes.RDS")
head(impact)
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.