## ----results = "asis", message = FALSE, warning = FALSE, eval = FALSE--------- # models <- ListModels(projectId) # model <- models[[1]] # trainingPredictions <- GetTrainingPredictionsForModel(model, dataSubset = DataSubset$All) # kable(head(trainingPredictions), longtable = TRUE, booktabs = TRUE, row.names = TRUE) ## ----results = "asis", echo = FALSE------------------------------------------- library(knitr) trainingPredictions <- readRDS("trainingPredictions.rds") kable(head(trainingPredictions), longtable = TRUE, booktabs = TRUE, row.names = TRUE) ## ----results = "asis", message = FALSE, warning = FALSE, eval = FALSE--------- # models <- ListModels(projectId) # model <- models[[1]] # jobId <- RequestTrainingPredictions(model, dataSubset = DataSubset$All) # # can run computations here while training predictions compute in the background # trainingPredictions <- GetTrainingPredictionsFromJobId(projectId, jobId) # blocks until job complete # kable(head(trainingPredictions), longtable = TRUE, booktabs = TRUE, row.names = TRUE) ## ----results = "asis", echo = FALSE------------------------------------------- library(knitr) trainingPredictions <- readRDS("trainingPredictions.rds") kable(head(trainingPredictions), longtable = TRUE, booktabs = TRUE, row.names = TRUE) ## ----results = "asis", message = FALSE, warning = FALSE, eval = FALSE--------- # trainingPredictions <- ListTrainingPredictions(projectId) # trainingPredictionId <- trainingPredictions[[1]]$id # trainingPrediction <- GetTrainingPredictions(projectId, trainingPredictionId) # kable(head(trainingPrediction), longtable = TRUE, booktabs = TRUE, row.names = TRUE) ## ----results = "asis", echo = FALSE------------------------------------------- trainingPrediction <- readRDS("trainingPrediction.rds") kable(head(trainingPrediction), longtable = TRUE, booktabs = TRUE, row.names = TRUE) ## ----results = "asis", message = FALSE, warning = FALSE, eval = FALSE--------- # DownloadTrainingPredictions(projectId, trainingPredictionId, "trainingPredictions.csv")