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Numerical Variables

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In this course, you will learn how to apply basic and more advanced feature engineering to tabular data with python, during this course,  we will see a range of different techniques and methods to handle many common cases within the data set, so in result, you will create great features so that your machine learning models can predict good results.

Feature Engineering with Python

## Definition
End of tail imputation is equivalent to arbitrary value imputation, but it automatically selects arbitrary values at the end of the variable distributions.


>This method works with numerical variables.

Arbitrary values are selected as follows:
- If the variable follows a normal distribution, we can use the mean plus or minus three times the standard deviation.
- If the variable is skewed, we can use the IQR proximity rule.

> The missing data values should be replaced by values calculated only on the train set.

Here is an example of the age variable that follows a normal distribution:


# Definition
End of tail imputation is equivalent to arbitrary value imputation, but it automatically selects arbitrary values at the end of the variable distributions.


End of tail imputation is a technique used to impute missing values in a numeric variable. We will talk about this method in this lesson while exploring an illustrative example and the code needed to apply this method in machine learning projects.


End of tail imputation

End of tail imputation is a technique used to impute missing values in a numeric variable. We will talk about this method in this lesson while exploring an illustrative example and the code needed to apply this method in machine learning projects.

Introduction

Variable Types

Common Concerns in Datasets

Handling & Imputing Missing Values

Encoding Categorical Variables

Transforming Variables

Variable Discretization

Handling Outliers

Feature Scaling

Engineering Geospatial Data

Handling Date-Time and Mixed Variables

Resampling Imbalanced Data

Advanced Feature Engineering Techniques

Conclusion

End of tail imputation

Definition