Scaling II
You'll now apply a scaler to the dataset, which is available for you as environment.
Remember that Scaling helps the algorithm converge faster, and avoids having one dominant feature heavily influence the outcomes.
Latihan ini merupakan bagian dari kursus
Analyzing IoT Data in Python
Instruksi latihan
- Initialize a
StandardScalerand store it assc. - Fit the scaler to
environment. - Scale
environmentand store the result asenviron_scaled. - Convert the scaled data back to a DataFrame, using the same columns and index than the original DataFrame.
Latihan interaktif langsung praktik
Cobalah latihan ini dengan melengkapi kode contoh ini.
# Initialize StandardScaler
sc = ____()
# Fit the scaler
sc.fit(____)
# Transform the data
environ_scaled = ____.____(____)
# Convert scaled data to DataFrame
environ_scaled = pd.DataFrame(____,
columns=____,
index=____)
print(environ_scaled.head())
plot_unscaled_scaled(environment, environ_scaled)