To craft a prediction graph, begin by preparing and cleaning your data, addressing missing values and categorical variables. Select an appropriate machine learning model and optimize its hyperparameters. Visualize your model’s predictions via graphs like scatter plots or ROC curves. Interpret these graphs to gain insights into model accuracy, precision, and recall. Employ software and tools to streamline the process, leveraging their strengths and addressing their limitations. Finally, assess model performance using relevant metrics to guide decision-making.
