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https://github.com/saymrwulf/prophet.git
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14d5028a73
* Add metrics for model validation * Update to reflect comments on Github * Change all_metrics() implementation to more sophisticated style * Update metrics functions * Remove redundant argument * Use v0.3 files for diagnostics.R and prophet.R * Use v0.3 file for man/predict.prophet.Rd * Change the interface and do some refactoring
60 lines
1.8 KiB
R
60 lines
1.8 KiB
R
library(prophet)
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context("Prophet metrics tests")
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## Makes R CMD CHECK happy due to dplyr syntax below
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globalVariables(c("y", "yhat"))
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DATA <- head(read.csv('data.csv'), 100)
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DATA$ds <- as.Date(DATA$ds)
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test_that("metrics_tests_using_model", {
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# Create dummy model
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m <- prophet(DATA)
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# Create metric data
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forecast <- predict(m, NULL)
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df <- na.omit(dplyr::inner_join(m$history, forecast, by="ds"))
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# Check all metrics wether it is equal to its definition
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y <- df$y
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yhat <- df$yhat
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expect_equal(me(m), mean(y-yhat))
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expect_equal(mse(m), mean((y-yhat)^2))
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expect_equal(rmse(m), sqrt(mean((y-yhat)^2)))
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expect_equal(mae(m), mean(abs(y-yhat)))
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expect_equal(mpe(m), 100*mean((y-yhat)/y))
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expect_equal(mape(m), 100*mean(abs((y-yhat)/y)))
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answer <- data.frame(
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me=me(m),
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mse=mse(m),
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rmse=rmse(m),
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mae=mae(m),
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mpe=mpe(m),
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mape=mape(m)
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)
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expect_equal(all_metrics(m), answer)
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})
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test_that("metrics_tests_using_simulated_historical_forecast", {
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#skip_if_not(Sys.getenv('R_ARCH') != '/i386')
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# Create dummy model
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m <- prophet(DATA)
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# Run simulated historical forecast
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df <- simulated_historical_forecasts(m, horizon = 3, units = 'days', k = 2, period = 3)
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# Check all metrics wether it is equal to its definition
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y <- df$y
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yhat <- df$yhat
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expect_equal(me(df=df), mean(y-yhat))
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expect_equal(mse(df=df), mean((y-yhat)^2))
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expect_equal(rmse(df=df), sqrt(mean((y-yhat)^2)))
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expect_equal(mae(df=df), mean(abs(y-yhat)))
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expect_equal(mpe(df=df), 100*mean((y-yhat)/y))
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expect_equal(mape(df=df), 100*mean(abs((y-yhat)/y)))
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answer <- data.frame(
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me=me(df=df),
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mse=mse(df=df),
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rmse=rmse(df=df),
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mae=mae(df=df),
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mpe=mpe(df=df),
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mape=mape(df=df)
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)
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expect_equal(all_metrics(df=df), answer)
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})
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