A model prediction is the anticipated outcome of a machine learning model based on the analysis of available data. It is the result of predictive models built on algorithms that determine trends, patterns, and insights within past and recent datasets, given the quality of assumptions and data analysis.
With model predictions, the unknown event is often in the future. However, there are cases when the event of interest is in the past or present.
Predictive modeling is generally used to determine future outcomes from data, involving algorithms trained iteratively over time to respond and adjust to new data. Two models are utilized to generate a prediction: classification and regression.
Classification models predict class membership, while regression models yield a numerical value. Below are the most commonly used algorithms to yield predictions:
Model predictions are used in the following situations:
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