jak spočítat rmse v lineární regresi python
actual = [0, 1, 2, 0, 3]
predicted = [0.1, 1.3, 2.1, 0.5, 3.1]
mse = sklearn.metrics.mean_squared_error(actual, predicted)
rmse = math.sqrt(mse)
print(rmse)
výpočet RMSE, Rsquared s stříšky v R
library(caret)
# datasets:
original = c( -2, 1, -3, 2, 3, 5, 4, 6, 5, 6, 7)
predicted = c(-1, -1, -2, 2, 3, 4, 4, 5, 5, 7, 7)
# caret package functions
RMSE(predicted, original)
R2(predicted, original, form = "traditional")
[1] 0.904534
calc_rmse v R
calc_rmse(df_all, date_min = NULL, center = F)