In 2021, a precise forecast of Iran Post's 2021-2022 income was achieved using ARIMA, with only a 1.5\% error. This approach was subsequently extended to estimate the income and traffic for 2022-2023.

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.

🔍✨ A machine learning project that predicts income based on various demographic factors using Random Forest and Gradient Boosting algorithms. Includes data preprocessing, hyperparameter tuning, and model evaluation with detailed performance metrics. 📊🤖

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.

Census income prediction by employing the power of supervised learning

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

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…

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 repository contains a model for predicting if an individual earns above or below an income threshold

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.

This project predicts whether an individual earns more than 50K using the Adult Income dataset. A Random Forest model is trained and evaluated, with explanations provided through DALEX and LIME for feature importance and model transparency.

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%.

Individual Machine Learning competition code as part of the 2019/20 Machine Learning module at Trinity College Dublin

Finding Donors for CharityML using supervised learners.

This repo stores the script, the data, and its description for the kernels published on kaggle.