R²
R-squared represents the proportion of variance explained by a regression model. It equals the square of the Pearson correlation coefficient and is used to evaluate the goodness of fit of a regression model.
Timeline (last 90 days)
On the training samples, the character regression model achieved an RMSE of 0.09 and an R² of 0.85.
When the prediction target has a large number of unobservable exogenous disturbances, a lower R² is theoretically inevitable, and the more critical engineering reference is whether the absolute errors MAE/RMSE fall within the process tolerance range.
Constructing features such as trend slope, trend consistency (number of consecutive months of increase or decrease, or R²), and the current value's position relative to an individual's long-term trend line can differentiate between growing and declining physicians.
R² (coefficient of determination) measures how well a trend line explains the actual data, with values ranging from 0 to 1; a value close to 1 indicates that a physician's prescribing behavior develops steadily along the trend.
All Facts (4)
On the training samples, the character regression model achieved an RMSE of 0.09 and an R² of 0.85.
50%UnverifiedWhen the prediction target has a large number of unobservable exogenous disturbances, a lower R² is theoretically inevitable, and the more critical engineering reference is whether the absolute errors MAE/RMSE fall within the process tolerance range.
50%UnverifiedConstructing features such as trend slope, trend consistency (number of consecutive months of increase or decrease, or R²), and the current value's position relative to an individual's long-term trend line can differentiate between growing and declining physicians.
50%UnverifiedR² (coefficient of determination) measures how well a trend line explains the actual data, with values ranging from 0 to 1; a value close to 1 indicates that a physician's prescribing behavior develops steadily along the trend.
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