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  • Is there a library function for Root mean square error (RMSE) in python?
    If you understand RMSE: (Root mean squared error), MSE: (Mean Squared Error) RMD (Root mean squared deviation) and RMS: (Root Mean Squared), then asking for a library to calculate this for you is unnecessary over-engineering All these can be intuitively written in a single line of code rmse, mse, rmd, and rms are different names for the same
  • Root mean square of a function in python - Stack Overflow
    i e the square root of the mean of the squared values of elements of y In numpy, you can simply square y, take its mean and then its square root as follows: rms = np sqrt(np mean(y**2)) So, for example:
  • Finding Root Mean Squared Error with Pandas dataframe
    Thank you! I made a slight tweak to the code that you posted I had to transform X_test using np reshape Also do you know the significance of using double brackets in pandas
  • python - Mean Squared Error in Numpy? - Stack Overflow
    This answer is not correct because when you square a numpy matrix, it will perform a matrix multiplication rathar square each element individualy Check my comment in Saullo Castro's answer (PS: I've tested it using Python 2 7 5 and Numpy 1 7 1) –
  • How do I calculate square root in Python? - Stack Overflow
    Arbitrary precision square root This variation uses string manipulations to convert a string which represents a decimal floating-point number to an int, calls math isqrt to do the actual square root extraction, and then formats the result as a decimal string math isqrt rounds down, so all produced digits are correct
  • python - How to express Root Mean Squared Error as a percentage . . .
    In the article, the author says 'The relative percentage of root mean square (RMS%) was used to evaluate the performance' This is what I want to compare my prediction to Currently I'm calculating the root mean square error, however I don't understand how to express this as a percentage


















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