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SE is calculated using two 1D arrays. The first array y contains the true result (reference) for each sample and the second array contains the model on p for the same sample. The error is calculated by subtracting each element in p from its analogous element in y and square the answer as described quation above. he program starts, the user is asked to enter the name of the file that contains the data. The file name is guaranteed not to exceed 20 ters. Then you should open the supplied file to read the data and calculate the RMSE. The data in the file is organized as follows: ne first line contains the size of the 1D array (i.e. denoted as N in the equation) ne second line contains the elements of y array followed by the content of the p array. ess than or equals zero or not an integer value, then the program should print Invalid Size e number of elements in the file should be 2*N(N for each array). Hence, if the number of elements in the file is less than 2*N, then the program print Few elements. Also if the number of elements in the file is more than 2*N then the program should print Many elements.

SE is calculated using two 1D arrays. The first array y contains the true result (reference) for each sample and the second array contains the model on p for the same sample. The error is calculated by subtracting each element in p from its analogous element in y and square the answer as described quation above. he program starts, the user is asked to enter the name of the file that contains the data. The file name is guaranteed not to exceed 20 ters. Then you should open the supplied file to read the data and calculate the RMSE. The data in the file is organized as follows: ne first line contains the size of the 1D array (i.e. denoted as N in the equation) ne second line contains the elements of y array followed by the content of the p array. ess than or equals zero or not an integer value, then the program should print Invalid Size e number of elements in the file should be 2*N(N for each array). Hence, if the number of elements in the file is less than 2*N, then the program print Few elements. Also if the number of elements in the file is more than 2*N then the program should print Many elements.

Computer Networking: A Top-Down Approach (7th Edition)
Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
Section: Chapter Questions
Problem R1RQ: What is the difference between a host and an end system? List several different types of end...
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Root Mean Square Error (RMSE) is a standard way to measure the error of a model in predicting quantitative data. Formally, it is defined as follows: RMSE = The RMSE is calculated using two 1D arrays. The first array y contains the true result (reference) for each sample and the second array contains the model prediction p for the same sample. The error is calculated by subtracting each element in p from its analogous element in y and square the answer as described in the equation above. When the program starts, the user is asked to enter the name of the file that contains the data. The file name is guaranteed not to exceed 20 characters. Then you should open the supplied file to read the data and calculate the RMSE. The data in the file is organized as follows: • The first line contains the size of the 1D array (i.e. denoted as N in the equation) • The second line contains the elements of y array followed by the content of the p array. If N is less than or equals zero or not an integer value, then the program should print Invalid Size Also, the number of elements in the file should be 2*N(N for each array). Hence, if the number of elements in the file is less than 2*N, then the program should print Few elements. Also if the number of elements in the file is more than 2*N then the program should print Many elements.
Transcribed Image Text:Root Mean Square Error (RMSE) is a standard way to measure the error of a model in predicting quantitative data. Formally, it is defined as follows: RMSE = The RMSE is calculated using two 1D arrays. The first array y contains the true result (reference) for each sample and the second array contains the model prediction p for the same sample. The error is calculated by subtracting each element in p from its analogous element in y and square the answer as described in the equation above. When the program starts, the user is asked to enter the name of the file that contains the data. The file name is guaranteed not to exceed 20 characters. Then you should open the supplied file to read the data and calculate the RMSE. The data in the file is organized as follows: • The first line contains the size of the 1D array (i.e. denoted as N in the equation) • The second line contains the elements of y array followed by the content of the p array. If N is less than or equals zero or not an integer value, then the program should print Invalid Size Also, the number of elements in the file should be 2*N(N for each array). Hence, if the number of elements in the file is less than 2*N, then the program should print Few elements. Also if the number of elements in the file is more than 2*N then the program should print Many elements.
Root Mean Square Error (RMSE) is a standard way to measure the error of a model in predicting quantitative data. Formally, it is defined as follows: RMSE The RMSE is calculated using two 1D arrays. The first array y contains the true result (reference) for each sample and the second array contains the model prediction p for the same sample. The error is calculated by subtracting each element in p from its analogous element in y and square the answer as described in the equation above. When the program starts, the user is asked to enter the name of the file that contains the data. The file name is guaranteed not to exceed 20 characters. Then you should open the supplied file to read the data and calculate the RMSE. The data in the file is organized as follows: • The first line contains the size of the 1D array (i.e. denoted as N in the equation) • The second line contains the elements of y array followed by the content of the p array. If N is less than or equals zero or not an integer value, then the program should print Invalid Size Also, the number of elements in the file should be 2*N(N for each array). Hence, if the number of elements in the file is less than 2*N, then the program should print Few elements. Also if the number of elements in the file is more than 2*N then the program should print Many elements.
Transcribed Image Text:Root Mean Square Error (RMSE) is a standard way to measure the error of a model in predicting quantitative data. Formally, it is defined as follows: RMSE The RMSE is calculated using two 1D arrays. The first array y contains the true result (reference) for each sample and the second array contains the model prediction p for the same sample. The error is calculated by subtracting each element in p from its analogous element in y and square the answer as described in the equation above. When the program starts, the user is asked to enter the name of the file that contains the data. The file name is guaranteed not to exceed 20 characters. Then you should open the supplied file to read the data and calculate the RMSE. The data in the file is organized as follows: • The first line contains the size of the 1D array (i.e. denoted as N in the equation) • The second line contains the elements of y array followed by the content of the p array. If N is less than or equals zero or not an integer value, then the program should print Invalid Size Also, the number of elements in the file should be 2*N(N for each array). Hence, if the number of elements in the file is less than 2*N, then the program should print Few elements. Also if the number of elements in the file is more than 2*N then the program should print Many elements.
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