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Please enable JavaScript in your browser settings or update your browser.Label Encoding of the Target Variable | Processing Categorical Data
course content

Course Content

Data Preprocessing

1. Brief Introduction

Data TypesData Processing MethodsDataset: Test and TrainingDeleting an "Extra" DataChanging the Data Type

2. Processing Quantitative Data

Data ScalingData Scaling vs Data NormalizationRemoving OutliersRemoving Missing ValuesData Augmentation: Synthetic Data

3. Processing Categorical Data

Methods for Encoding the Categorical DataOne-Hot EncodingOrdinal EncodingLabel Encoding of the Target VariableChallenge

4. Time Series Data Processing

Data Type ConversionData CleaningStationarityDenoisingTrain/Test Split & Cross ValidationChallenge

5. Feature Engineering

Technique IdeaRealizationFeature Extraction from TextFeature Extraction from ImagesFeature Extraction from Time SeriesChallenge

6. Moving on to Tasks

Challenge 1Challenge 2Challenge 3

Data Preprocessing

Label Encoding of the Target VariableLabel 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:

Task

Read the dataset 'salary_and_gender.csv' and encode the output column 'Gender' with label encoding.

Everything was clear?

Section 3. Chapter 4
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course content

Course Content

Data Preprocessing

1. Brief Introduction

Data TypesData Processing MethodsDataset: Test and TrainingDeleting an "Extra" DataChanging the Data Type

2. Processing Quantitative Data

Data ScalingData Scaling vs Data NormalizationRemoving OutliersRemoving Missing ValuesData Augmentation: Synthetic Data

3. Processing Categorical Data

Methods for Encoding the Categorical DataOne-Hot EncodingOrdinal EncodingLabel Encoding of the Target VariableChallenge

4. Time Series Data Processing

Data Type ConversionData CleaningStationarityDenoisingTrain/Test Split & Cross ValidationChallenge

5. Feature Engineering

Technique IdeaRealizationFeature Extraction from TextFeature Extraction from ImagesFeature Extraction from Time SeriesChallenge

6. Moving on to Tasks

Challenge 1Challenge 2Challenge 3

Data Preprocessing

Label Encoding of the Target VariableLabel 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:

Task

Read the dataset 'salary_and_gender.csv' and encode the output column 'Gender' with label encoding.

Everything was clear?

Section 3. Chapter 4
toggle bottom row
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