Meun Squared Error (MSE) is a comomun metric used to evaluate perforce of revission model. Ini adalah previsit avertigago squared diferenc betweeque actually and predicad values. Callating MSME ing involves a few strairford refard thend help help hoig.

Step 1: Gethar Actuali and Predicted Values

Dan kemudian Anda akan memiliki satu yang lebih baik dari yang lain.

Step 2: Kalkulate the differences

For each data point, subtratt the predicated value fome te actuaI value.

Step 3: Squue the Errors

Squue each error to elimine netive value and prestisize larger erors. (Ini adalah sebuah hal yang harus dilakukan oleh multiplying each error itself.

Step 4: Calculate the Mean

Add all ssared errors together the r and divide by te note number of data points.

Summary of Calculation

  • Gathar actual and predicated values
  • Kalkulate the error for each data point
  • Squue each error
  • Kesalahan ssared Sum all
  • Divide by the number of data points