What type of analysis does a predictive model rely on?

A predictive model relies on statistical and machine learning analysis to forecast future events based on current and historical data. This approach leverages both statistical techniques and algorithms derived from machine learning to identify patterns and relationships within the data. By utilizing these methods, predictive models can draw inferences from data, making it possible to estimate future outcomes more accurately.

Statistical analysis helps in understanding the data distributions and relationships among variables, while machine learning techniques enhance the model's ability to learn from data continuously and adapt to new information. Together, these analyses enable the model to predict trends, identify risks, and make informed decisions based on the insights gleaned from the data. This combination is crucial for tasks such as demand forecasting, risk assessment, and customer behavior prediction.