Calibration
Calibration is the process of adjusting or standardizing a measuring instrument or device to ensure its accuracy and precision. In data science, calibration is used to ensure that the output of a model or algorithm is accurate and reliable. This is done by comparing the predicted values of the model to the actual values and adjusting the model parameters accordingly. Calibration is important in machine learning, where models are trained on a set of data and then used to make predictions on new data. If the model is not calibrated properly, it may overfit or underfit the data, leading to inaccurate predictions. Calibration is also used in experimental design, where it is used to ensure that the measurements taken are accurate and reliable. This is done by comparing the measurements to a known standard and adjusting the instrument accordingly.
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