Imbalanced Classification with the Adult Income Dataset

Many binary classification tasks do not have an equal number of examples from each class, e.g. the class distribution is skewed or imbalanced. A popular example is the adult income dataset that involves predicting personal income levels as above or below $50,000 per year based on personal details such as relationship and education level. There are many more cases of incomes less than $50K than above $50K, although the skew is not severe. This means that techniques for imbalanced classification can be used whilst model performance can still be reported using classification accuracy, as is used with balanced classification problems. In this tutorial, you will discover how to develop and evaluate a model for the imbalanced adult income classification dataset. Develop an Imbalanced Classification Model to Predict Income Photo by Kirt Edblom, some rights reserved.