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Add scaled MSE to regression evaluation metrics #297

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Mar 6, 2024
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Add scaled MSE to regression evaluation metrics #297

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5c15cac
Add scaled MSE to regression evaluation metrics
koenderks Mar 6, 2024
ea3c04e
Update help files
koenderks Mar 6, 2024
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7 changes: 5 additions & 2 deletions R/commonMachineLearningRegression.R
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Expand Up @@ -483,7 +483,7 @@
table$dependOn(options = c(.mlRegressionDependencies(options), "validationMeasures"))
table$addColumnInfo(name = "measures", title = "", type = "string")
table$addColumnInfo(name = "values", title = gettext("Value"), type = "string")
measures <- c("MSE", "RMSE", "MAE / MAD", "MAPE", "R\u00B2")
measures <- c("MSE", gettext("MSE(scaled)"), "RMSE", "MAE / MAD", "MAPE", "R\u00B2")
table[["measures"]] <- measures
jaspResults[["validationMeasures"]] <- table
if (!ready) {
Expand All @@ -495,11 +495,14 @@
obs <- predDat[["obs"]]
pred <- predDat[["pred"]]
mse <- round(regressionResult[["testMSE"]], 3)
obs_scaled <- (obs - mean(obs)) / sd(obs)
pred_scaled <- (pred - mean(pred)) / sd(pred)
mse_scaled <- round(mean((obs_scaled - pred_scaled)^2), 3)
rmse <- round(sqrt(mse), 3)
mae <- round(mean(abs(obs - pred)), 3)
mape <- paste0(round(mean(abs((obs - pred) / obs)) * 100, 2), "%")
r_squared <- round(cor(obs, pred)^2, 3)
values <- c(mse, rmse, mae, mape, r_squared)
values <- c(mse, mse_scaled, rmse, mae, mape, r_squared)
table[["values"]] <- values
if (is.na(r_squared)) {
table$addFootnote(gettextf("R%s cannot be computed due to lack of variance in the predictions.</i>", "\u00B2"))
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2 changes: 1 addition & 1 deletion tests/testthat/test-mlregressionboosting.R
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Expand Up @@ -103,7 +103,7 @@ test_that("Boosting Regression table results match", {
test_that("Evaluation Metrics table results match", {
table <- results[["results"]][["validationMeasures"]][["data"]]
jaspTools::expect_equal_tables(table,
list("MSE", 0.28, "RMSE", 0.529, "MAE / MAD", 0.425, "MAPE", "3.33%",
list("MSE", 0.28, "MSE(scaled)", 0.374, "RMSE", 0.529, "MAE / MAD", 0.425, "MAPE", "3.33%",
"R<unicode><unicode>", 0.652))
})

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2 changes: 1 addition & 1 deletion tests/testthat/test-mlregressiondecisiontree.R
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Expand Up @@ -103,6 +103,6 @@ test_that("Additive Explanations for Predictions of Test Set Cases table results
test_that("Model Performance Metrics table results match", {
table <- results[["results"]][["validationMeasures"]][["data"]]
jaspTools::expect_equal_tables(table,
list("MSE", 0.18, "RMSE", 0.424, "MAE / MAD", 0.354, "MAPE", "6.01%",
list("MSE", 0.18, "MSE(scaled)", 0.349, "RMSE", 0.424, "MAE / MAD", 0.354, "MAPE", "6.01%",
"R<unicode>", 0.671))
})
2 changes: 1 addition & 1 deletion tests/testthat/test-mlregressionknn.R
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Expand Up @@ -79,7 +79,7 @@ test_that("K-Nearest Neighbors Regression table results match", {
test_that("Model Performance Metrics table results match", {
table <- results[["results"]][["validationMeasures"]][["data"]]
jaspTools::expect_equal_tables(table,
list("MSE", 0.379, "RMSE", 0.616, "MAE / MAD", 0.512, "MAPE", "3.98%",
list("MSE", 0.379, "MSE(scaled)", 0.583, "RMSE", 0.616, "MAE / MAD", 0.512, "MAPE", "3.98%",
"R<unicode>", 0.49))
})

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2 changes: 1 addition & 1 deletion tests/testthat/test-mlregressionlinear.R
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Expand Up @@ -76,6 +76,6 @@ test_that("Additive Explanations for Predictions of Test Set Cases table results
test_that("Model Performance Metrics table results match", {
table <- results[["results"]][["validationMeasures"]][["data"]]
jaspTools::expect_equal_tables(table,
list("MSE", 0.079, "RMSE", 0.281, "MAE / MAD", 0.228, "MAPE", "8.08%",
list("MSE", 0.079, "MSE(scaled)", 0.023, "RMSE", 0.281, "MAE / MAD", 0.228, "MAPE", "8.08%",
"R<unicode>", 0.976))
})
2 changes: 1 addition & 1 deletion tests/testthat/test-mlregressionneuralnetwork.R
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Expand Up @@ -52,7 +52,7 @@ test_that("Neural Network Regression table results match", {
test_that("Model Performance Metrics table results match", {
table <- results[["results"]][["validationMeasures"]][["data"]]
jaspTools::expect_equal_tables(table,
list("MSE", 0.089, "RMSE", 0.298, "MAE / MAD", 0.243, "MAPE", "4.18%",
list("MSE", 0.089, "MSE(scaled)", 0.156, "RMSE", 0.298, "MAE / MAD", 0.243, "MAPE", "4.18%",
"R<unicode>", 0.845))
})

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2 changes: 1 addition & 1 deletion tests/testthat/test-mlregressionrandomforest.R
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Expand Up @@ -107,7 +107,7 @@ test_that("Feature Importance Metrics table results match", {
test_that("Evaluation Metrics table results match", {
table <- results[["results"]][["validationMeasures"]][["data"]]
jaspTools::expect_equal_tables(table,
list("MSE", 0.355, "RMSE", 0.596, "MAE / MAD", 0.473, "MAPE", "3.71%",
list("MSE", 0.355, "MSE(scaled)", 0.531, "RMSE", 0.596, "MAE / MAD", 0.473, "MAPE", "3.71%",
"R<unicode><unicode>", 0.528))
})

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2 changes: 1 addition & 1 deletion tests/testthat/test-mlregressionregularized.R
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Expand Up @@ -93,7 +93,7 @@ test_that("Regularized Linear Regression table results match", {
test_that("Model Performance Metrics table results match", {
table <- results[["results"]][["validationMeasures"]][["data"]]
jaspTools::expect_equal_tables(table,
list("MSE", 0.316, "RMSE", 0.562, "MAE / MAD", 0.428, "MAPE", "3.34%",
list("MSE", 0.316, "MSE(scaled)", 0.504, "RMSE", 0.562, "MAE / MAD", 0.428, "MAPE", "3.34%",
"R<unicode>", 0.549))
})

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2 changes: 1 addition & 1 deletion tests/testthat/test-mlregressionsvm.R
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Expand Up @@ -194,6 +194,6 @@ test_that("Additive Explanations for Predictions of Test Set Cases table results
test_that("Model Performance Metrics table results match", {
table <- results[["results"]][["validationMeasures"]][["data"]]
jaspTools::expect_equal_tables(table,
list("MSE", 0.079, "RMSE", 0.281, "MAE / MAD", 0.234, "MAPE", "4.05%",
list("MSE", 0.079, "MSE(scaled)", 0.149, "RMSE", 0.281, "MAE / MAD", 0.234, "MAPE", "4.05%",
"R<unicode>", 0.852))
})
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