Label Encoding of the Target Variable
Let's go straight to the main thing - label encoding implements everything the same as ordinal encoder, but:
- Methods work with different data dimensions;
- The order of the categories is not important for label encoding.
How to use this method in Python:
1234567891011121314from sklearn.preprocessing import LabelEncoder import pandas as pd # Simple categorical variable fruits = pd.Series(['apple', 'orange', 'banana', 'banana', 'apple', 'orange', 'banana']) # Create label encoder object le = LabelEncoder() # Fit and transform the categorical variable using label encoding fruits_encoded = le.fit_transform(fruits) # Print the encoded values print(fruits_encoded)
Swipe to start coding
Read the dataset 'salary_and_gender.csv'
and encode the output column 'Gender'
with label encoding.
Soluzione
Grazie per i tuoi commenti!
single
Chieda ad AI
Chieda ad AI
Chieda pure quello che desidera o provi una delle domande suggerite per iniziare la nostra conversazione
Awesome!
Completion rate improved to 3.33Awesome!
Completion rate improved to 3.33
Label Encoding of the Target Variable
Let's go straight to the main thing - label encoding implements everything the same as ordinal encoder, but:
- Methods work with different data dimensions;
- The order of the categories is not important for label encoding.
How to use this method in Python:
1234567891011121314from sklearn.preprocessing import LabelEncoder import pandas as pd # Simple categorical variable fruits = pd.Series(['apple', 'orange', 'banana', 'banana', 'apple', 'orange', 'banana']) # Create label encoder object le = LabelEncoder() # Fit and transform the categorical variable using label encoding fruits_encoded = le.fit_transform(fruits) # Print the encoded values print(fruits_encoded)
Swipe to start coding
Read the dataset 'salary_and_gender.csv'
and encode the output column 'Gender'
with label encoding.
Soluzione
Grazie per i tuoi commenti!
single
Awesome!
Completion rate improved to 3.33
Label Encoding of the Target Variable
Scorri per mostrare il menu
Let's go straight to the main thing - label encoding implements everything the same as ordinal encoder, but:
- Methods work with different data dimensions;
- The order of the categories is not important for label encoding.
How to use this method in Python:
1234567891011121314from sklearn.preprocessing import LabelEncoder import pandas as pd # Simple categorical variable fruits = pd.Series(['apple', 'orange', 'banana', 'banana', 'apple', 'orange', 'banana']) # Create label encoder object le = LabelEncoder() # Fit and transform the categorical variable using label encoding fruits_encoded = le.fit_transform(fruits) # Print the encoded values print(fruits_encoded)
Swipe to start coding
Read the dataset 'salary_and_gender.csv'
and encode the output column 'Gender'
with label encoding.
Soluzione
Grazie per i tuoi commenti!