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.
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Completion rate improved to 3.33Label 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.
Oplossing
Schakel over naar desktop voor praktijkervaringGa verder vanaf waar je bent met een van de onderstaande optiesBedankt voor je feedback!
single
Awesome!
Completion rate improved to 3.33Label Encoding of the Target Variable
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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.
Oplossing
Schakel over naar desktop voor praktijkervaringGa verder vanaf waar je bent met een van de onderstaande optiesBedankt voor je feedback!
