Census income Prediction

Keywords: Census , income

Background

The Adult Census Income prediction using ANN is a popular dataset where one must predict income levels like whether it exceeds $50K or not. The goal is to build a model that can accurately predict an individual's income level based on their demographic features. The major challenge in this dataset is to analyze the various features like values and categorical variables. The problem statement for this work is to develop a predictive model using Artificial Neural Networks (ANN) to accurately classify whether an individual's income exceeds $50K based on their demographic attributes. Here, Artificial Neural Networks, which is a technique that can observe the complex and underlying patterns in the data, is used to deal with the challenges. The model will be trained on the census income prediction dataset. Finally, the results achieved using ANN model show a fair rate of accuracy which is 72% in predicting the income levels of the people based on their given features. The model demonstrates its ability to effectively learn from the dataset and make accurate predictions, thereby assisting in identifying individuals with high income potential based on their demographic attributes.

Aim & Objectives

Aim
To Predict the income of Census Data Using DL Methods
Objective
Build a deep learning model to predict income levels using census data.
Train the model with diverse features for accurate income classification.
Evaluate model's efficacy to provide reliable income predictions through DL techniques.

Research Methodology

ANN Technique used

Software & Tools

Jupyter, Google Collab

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