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How to Do Sequence Padding and One-Hot Encoding of Independent Variables

Sequence Padding and One-Hot Encoding

Condition for Sequence Padding and One-Hot Encoding

  • Description:
    Sequence Padding: This technique is used to adjust the length of input sequences to a fixed size by adding padding values (usually zeros) to ensure all sequences are equal in length.

    One-Hot Encoding: This technique is used to convert categorical variables into a binary matrix, where each category is represented by a unique column with a 1 for presence and 0 for absence.
Step-by-Step Process
  • Sequence Padding:
    Import libraries like keras.preprocessing.sequence to handle sequence padding.
  • Prepare the Sequences:
    Create a list of sequences that you want to pad.
  • Pad Sequences:
    Use the pad_sequences() function to pad the sequences to a fixed length.
  • One-Hot Encoding:
    Use OneHotEncoder from sklearn.preprocessing or pandas.get_dummies() to convert categorical data into a binary matrix.
Sample Source Code
  • # Code for Padding sequence

    from keras.preprocessing.sequence import pad_sequences

    sequences = [
    [1, 2, 3, 4, 5],
    [6, 7, 8],
    [9, 10, 11, 12],
    [13, 14],
    [15, 16, 17, 18, 19, 20]
    ]

    # Padding sequences to have the same length
    padded_sequences = pad_sequences(sequences, maxlen=6, padding='post', truncating='post')

    print("Padded Sequences:")
    print(padded_sequences)


    # Code for One-hot encoding
    import pandas as pd
    from sklearn.preprocessing import OneHotEncoder

    categories = ['dog', 'cat', 'dog', 'bird', 'cat', 'dog', 'bird', 'cat']

    categories_reshaped = pd.DataFrame(categories, columns=['Animal'])

    encoder = OneHotEncoder(sparse_output=False)

    # Fit and transform the data to obtain one-hot encoded values
    encoded_data = encoder.fit_transform(categories_reshaped)

    df_encoded = pd.DataFrame(encoded_data, columns=encoder.categories_[0])

    print("\nOne-Hot Encoded Data:")
    print(df_encoded)
Screenshots
  • Sequence Padding and One-Hot Encoding Output