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A prediction model that uses logistic regression and gradient boosting to classify population income.

License: MIT License

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machine-learning machine-learning-algorithms logistic-regression gradient-boosting gradient-boosting-machine classification classification-model classification-algorithm prediction-algorithm feature-engineering exploratory-data-analysis data-analysis exploratory-data-visualizations data-science

adult-income-prediction's Introduction

Adult Income Prediction

A prediction model to determine if a person's income is over $50,000 a year.

Dataset

The dataset is extracted from the 1994 Census database and is available on the UCI repository. The size of the dataset is 48,842 rows and includes 14 attributes such as age, gender, occupation, number of hours the individual works per week, etc.

Approach

  • Exploratory data analysis (uni-variate and bi-variate)
  • Data preprocessing (deduplication, handling missing values)
  • Classification using logistic regression
  • Classification using a gradient boosting machine
  • Feature engineering

Results

Algorithm Accuracy Area under the curve
Logistic regression 81.63% 0.862
Gradient boosting machine 82.58% 0.881

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