Skalierung und Transformationen

Feature Engineering für Machine Learning in Python

Robert O'Callaghan

Data Scientist

Daten skalieren

Feature Engineering für Machine Learning in Python

Min-Max-Skalierung

Minmax shrink

Feature Engineering für Machine Learning in Python

Min-Max-Skalierung

Feature Engineering für Machine Learning in Python

Min-Max-Skalierung in Python

from sklearn.preprocessing import MinMaxScaler

scaler = MinMaxScaler()

scaler.fit(df[['Age']])

df['normalized_age'] = scaler.transform(df[['Age']])
Feature Engineering für Machine Learning in Python

Standardisierung

Feature Engineering für Machine Learning in Python

Standardisierung in Python

from sklearn.preprocessing import StandardScaler

scaler = StandardScaler()

scaler.fit(df[['Age']])

df['standardized_col'] = scaler\
                        .transform(df[['Age']])
Feature Engineering für Machine Learning in Python

Log-Transformation

log image

Feature Engineering für Machine Learning in Python

Log-Transformation in Python

from sklearn.preprocessing import PowerTransformer

log = PowerTransformer()

log.fit(df[['ConvertedSalary']])

df['log_ConvertedSalary'] = 
     log.transform(df[['ConvertedSalary']])
Feature Engineering für Machine Learning in Python

Abschlussfolie

Feature Engineering für Machine Learning in Python

Preparing Video For Download...