AutoFE-X brings automated feature engineering, data diagnostics, leakage detection, benchmarking, and feature lineage into a unified toolkit designed for modern ML workflows. It acts as a structured ...

The study explores the effectiveness of the ARIMA(3,1,3) model in predicting market trends, specifically accounting for macroeconomic shifts like the 2026 CPI base year updates. Stationarity ...

Time series data often exhibits trends and seasonality, making it non-stationary. Stationarity is essential for accurate forecasting, as time series models assume independence between data points.

Time series data consists of data points collected over time, used for predicting future responses based on past information. Accurate forecasting requires a stationary time series, minimising the ...