Dockerfile.tar.gz

Numerical Variables

Default Job

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
Probability Ratio Encoding is similar to Weight of Evidence (WOE), with the only difference being that we only use the ratio of the probabilities. For each label, we calculate the mean of target=1, that is, the probability of being 1 (P (1)), and also the probability of the target=0 (P (0)). Then, we calculate the ratio = P (1)/P (0) and replace the labels with that ratio.

Here is an example using probability ratio encoding:

# Definition
Probability Ratio Encoding is similar to Weight of Evidence (WOE), with the only difference being that we only use the ratio of the probabilities. For each label, we calculate the mean of target=1, that is, the probability of being 1 (P (1)), and also the probability of the target=0 (P (0)). Then, we calculate the ratio = P (1)/P (0) and replace the labels with that ratio.

Here is an example using probability ratio encoding:

The purpose of this lesson is to explore another encoding technique called Probability Ratio Encoding, which is suitable for classification problems. We will also explore its pros and cons and learn how to implement it in a few lines of code.


Probability ratio encoding

The purpose of this lesson is to explore another encoding technique called Probability Ratio Encoding, which is suitable for classification problems. We will also explore its pros and cons and learn how to implement it in a few lines of code.

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

Probability ratio encoding

Definition