Challenge
Aufgabe
Swipe to start coding
Create an autoregressive model to predict the dataset aapl.csv
. After, print the results and the model error.
- Read the
aapl.csv
dataset. - Create an autoregressive model (
AutoReg
) with 3 lags for theX
data and assign it to themodel
variable. - Fit model to the data and assign it to the
model_fit
variable. - Predict the first 30 values.
- Visualize the results: display the first 30 values of
X
within the first call of theprint()
function, and first 30 values of thepredictions
within the second call. - Calculate the RMSE (square root of the mean squared error) and display it.
Lösung
War alles klar?
Danke für Ihr Feedback!
Abschnitt 4. Kapitel 5
single
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Completion rate improved to 3.85
Challenge
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Aufgabe
Swipe to start coding
Create an autoregressive model to predict the dataset aapl.csv
. After, print the results and the model error.
- Read the
aapl.csv
dataset. - Create an autoregressive model (
AutoReg
) with 3 lags for theX
data and assign it to themodel
variable. - Fit model to the data and assign it to the
model_fit
variable. - Predict the first 30 values.
- Visualize the results: display the first 30 values of
X
within the first call of theprint()
function, and first 30 values of thepredictions
within the second call. - Calculate the RMSE (square root of the mean squared error) and display it.
Lösung
War alles klar?
Danke für Ihr Feedback!
Awesome!
Completion rate improved to 3.85Abschnitt 4. Kapitel 5
single