Covers: theory of Imbalanced Classification
Estimated time needed to finish: 9 minutes
Questions this item addresses:
- What is a classification problem?
- Why imbalanced datasets are a challenge for classification algorithms?
- Which ones are examples of imbalanced classification problems?
How to use this item?
Read the article. The resource presents clarification of what is an imbalanced dataset, why this is a challenge for classification and some examples of imbalanced classification problems.
Author(s) / creator(s) / reference(s)
Jason Brownlee
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Working with imbalanced classification (binary case)
Contributors
- Objectives
- The user of this short list will learn about the different techniques to handle imbalanced datasets and the importance of model calibration
- Potential Use Cases
- You are working with imbalanced datasets, for example fraud detection.
- Who is This For ?
- INTERMEDIATEPractitioners working with imbalanced datasets
Click on each of the following annotated items to see details.
ARTICLE 1. A Gentle Introduction to Imbalanced Classification
- What is a classification problem?
- Why imbalanced datasets are a challenge for classification algorithms?
- Which ones are examples of imbalanced classification problems?
9 minutes
VIDEO 2. Machine Learning Classification How to Deal with Imbalanced Data
- Why it is important to deal with imbalanced data?
- How to use SMOTE?
10 minutes
ARTICLE 3. 7 Techniques to Handle Imbalanced Data
- Which evaluation metrics can be used for an imbalanced dataset?
- How can the dataset be resample?
- Which techniques can be applied to imbalanced datasets?
9 minutes
ARTICLE 4. Dealing with Imbalanced Data
- Which metrics are used with imbalanced datasets?
- How to oversample the data?
- How to under sample the data?
5 minutes
ARTICLE 5. Classifier calibration
- Why calibration is important?
- How to create a probability density plot of your model?
- How to calibrate the model?
7 minutes
ARTICLE 6. How to Calibrate Probabilities for Imbalanced Classification
- Why uncalibrated probabilities are a problem?
- How to calibrate probabilities?
- How to calibrate SVM?
- How to calibrate KNN?
15 minutes
Concepts Covered
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