There are 1 repository under income-prediction topic.
Predict whether income exceeds $50K/yr based on census data.
To build a classification methodology to determine whether a person makes over 50K per year.
Census income prediction by employing the power of supervised learning
a predictive model to determine the income level for people in US. Imputed and manipulated large and high dimensional data using data.table in R. Performed SMOTE as the dataset is highly imbalanced. Developed naïve Bayes, XGBoost and SVM models for classification
Basic Machine Learning Classifiers with scikit-learn.
This project focuses on predicting the income of individuals based on a diverse set of demographic and socio-economic features. Using the Adult Income dataset, I used a Random Forest model to address this classification task.
I analyze and explore US Census Bureau Data using Data Visualization techniques to identify salient features useful for predicting an individual's income level. We use those relevant features and multiple classification methods (Decision-Tree, SVM, and K-Nearest Neighbor) to predict the income level for unknown individuals. Our client is a local University who wants to use income as the key demographic to decide criteria for marketing its degree programs. Each classifier explored has an accuracy of over 85%.
Building a Classification model to predict whether a person's annual Income is more than $50K or below $50K
Building an Income Prediction System Using Machine Learning Model and Deploying it as a Web App
Income Tax Calculator is a comprehensive web application designed to provide net income estimates after federal and state taxes. Built with TypeScript, and NextJs, it offers detailed breakdowns for both hourly and salaried income types.
Predict whether income exceeds $50K/yr based on census data.
This repo stores the script, the data, and its description for the kernels published on kaggle.
This project aims to predict the income bracket of individuals based on a variety of features, and presents a holistic comparative analysis between multiple machine learning algorithms through hyperparameter optimization on a binary classification problem.
Data science project for feature engineering and classification using as case study the Census Income dataset
TCD Machine Learning Kaggle Individual Competition in which one predicted the income of people with Machine Learning using pandas, numpy and sklearn.
Individual Machine Learning competition code as part of the 2019/20 Machine Learning module at Trinity College Dublin
Project that focuses on find the determinants of income using the dataset: https://www.kaggle.com/datasets/fedesoriano/gender-pay-gap-dataset
Udacity Machine Learning Engineer Nanodegree Program Capstone Project
In this project, I have predicted Income between two categories based on an individual's demographic and employment details using Logistic regression.
TCD ML Comp. 2019/20 - Income Prediction (Ind.)
Income Prediction Model deployed as Flask app
Finding Donors for CharityML using supervised learners.
Exploratory Data Analysis and Classification Modelling of the Adult Income Dataset aka the Census Income Dataset
A deep learning model capable of predicting your income based on Age, Sex, Race, Education, Marital-Status, working hours/week, native country, and occupation with an accuracy of almost 85%.
CS7CS4- Machine Learning- Income Prediction- Kaggle Competition
To predict whether the income of the individual is above or below 50 K