D. mean positive error<\/strong>.<\/p>\nMean positive error is the average of the absolute values of the positive differences between computed and desired outcome values. It is a measure of the average amount by which the computed values are too high.<\/p>\n
Root mean squared error (RMSE) is the square root of the mean squared error. It is a measure of the average squared difference between computed and desired outcome values.<\/p>\n
Mean squared error (MSE) is the average of the squared differences between computed and desired outcome values. It is a measure of the average squared error between the computed values and the desired values.<\/p>\n
Mean absolute error (MAE) is the average of the absolute values of the differences between computed and desired outcome values. It is a measure of the average absolute error between the computed values and the desired values.<\/p>\n
Here is a table that summarizes the differences between the four measures:<\/p>\n
| Measure | Formula | Interpretation |
\n|—|—|—|
\n| Root mean squared error (RMSE) | $\\sqrt{\\frac{\\sum_{i=1}^n (y_i – \\hat{y}i)^2}{n}}$ | The square root of the mean squared error. It is a measure of the average squared error between the computed values and the desired values. |
\n| Mean squared error (MSE) | $\\frac{\\sum<\/em>{i=1}^n (y_i – \\hat{y}i)^2}{n}$ | The average of the squared differences between the computed and desired outcome values. It is a measure of the average squared error between the computed values and the desired values. |
\n| Mean absolute error (MAE) | $\\frac{\\sum<\/em>{i=1}^n |y_i – \\hat{y}i|}{n}$ | The average of the absolute values of the differences between the computed and desired outcome values. It is a measure of the average absolute error between the computed values and the desired values. |
\n| Mean positive error (MPE) | $\\frac{\\sum<\/em>{i=1}^n |y_i – \\hat{y}i|}{n} \\cdot \\frac{1}{n} \\sum<\/em>{i=1}^n \\mathbb{I}(y_i – \\hat{y}_i > 0)$ | The average of the absolute values of the positive differences between the computed and desired outcome values. It is a measure of the average amount by which the computed values are too high. |<\/p>\n","protected":false},"excerpt":{"rendered":"[amp_mcq option1=”root mean squared error” option2=”mean squared error” option3=”mean absolute error” option4=”mean positive error” correct=”option4″]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[729],"tags":[],"class_list":["post-51297","post","type-post","status-publish","format-standard","hentry","category-machine-learning","no-featured-image-padding"],"yoast_head":"\n
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