How to find execution time of classification algorithms in R? [duplicate]

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get execution time in milliseconds in R

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I am running a naive bayes classifcation algorithm in R. I want to calculate the execution time of the algorithm.
Shall i use

Start_time <- proc.time()

{                

  #execution of naive bayes classifier

}

End_time <- proc_time()

Exec_time = End_time - Start_time

to find the execution time.
Is it the right way to calculate the execution time of an algorithm?

edited Nov 21 at 19:01

42-

210k14249394

asked Nov 21 at 18:37

raji sadhu

marked as duplicate by Henrik r
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Nov 21 at 20:52

This question has been asked before and already has an answer. If those answers do not fully address your question, please ask a new question.

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up vote
0
down vote

favorite

This question already has an answer here:

get execution time in milliseconds in R

3 answers

I am running a naive bayes classifcation algorithm in R. I want to calculate the execution time of the algorithm.
Shall i use

Start_time <- proc.time()

{                

  #execution of naive bayes classifier

}

End_time <- proc_time()

Exec_time = End_time - Start_time

to find the execution time.
Is it the right way to calculate the execution time of an algorithm?

edited Nov 21 at 19:01

42-

210k14249394

asked Nov 21 at 18:37

raji sadhu

marked as duplicate by Henrik r
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Nov 21 at 20:52

This question has been asked before and already has an answer. If those answers do not fully address your question, please ask a new question.

add a comment |

up vote
0
down vote

favorite

This question already has an answer here:

get execution time in milliseconds in R

3 answers

I am running a naive bayes classifcation algorithm in R. I want to calculate the execution time of the algorithm.
Shall i use

Start_time <- proc.time()

{                

  #execution of naive bayes classifier

}

End_time <- proc_time()

Exec_time = End_time - Start_time

to find the execution time.
Is it the right way to calculate the execution time of an algorithm?

edited Nov 21 at 19:01

42-

210k14249394

asked Nov 21 at 18:37

raji sadhu

This question already has an answer here:

get execution time in milliseconds in R

3 answers

I am running a naive bayes classifcation algorithm in R. I want to calculate the execution time of the algorithm.
Shall i use

Start_time <- proc.time()

{                

  #execution of naive bayes classifier

}

End_time <- proc_time()

Exec_time = End_time - Start_time

to find the execution time.
Is it the right way to calculate the execution time of an algorithm?

This question already has an answer here:

get execution time in milliseconds in R

3 answers

r execution-time

edited Nov 21 at 19:01

42-

210k14249394

asked Nov 21 at 18:37

raji sadhu

edited Nov 21 at 19:01

42-

210k14249394

asked Nov 21 at 18:37

raji sadhu

edited Nov 21 at 19:01

42-

210k14249394

edited Nov 21 at 19:01

42-

210k14249394

edited Nov 21 at 19:01

42-

210k14249394

asked Nov 21 at 18:37

raji sadhu

asked Nov 21 at 18:37

raji sadhu

asked Nov 21 at 18:37

raji sadhu

marked as duplicate by Henrik r
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Nov 21 at 20:52

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Nov 21 at 20:52

This question has been asked before and already has an answer. If those answers do not fully address your question, please ask a new question.

add a comment |

1 Answer
1

active

oldest

votes

up vote
0
down vote

You can use package microbenchmark or rbenchmark to test code.

First define a function:

myfunction <- function(){}

then define how many times should run the function

n <- 10

Here is an example using microbenchmark:

microbenchmark::microbenchmark(myfunction(),times=n) #run your function "n" times

Here is an example using rbenchmark:

rbenchmark::benchmark(myfunction(),replications=n) #run your function "n" times

For both packages you can get the result using operator <-. For example:

microbenchmark::microbenchmark(a<-myfunction(),times=n) # result is in variable "a"

rbenchmark::rbenchmark(a<-myfunction(),times=n) # result is in variable "a"

answered Nov 21 at 19:48

Csd

29819

add a comment |

1 Answer
1

active

oldest

votes

1 Answer
1

active

oldest

votes

up vote
0
down vote

You can use package microbenchmark or rbenchmark to test code.

First define a function:

myfunction <- function(){}

then define how many times should run the function

n <- 10

Here is an example using microbenchmark:

microbenchmark::microbenchmark(myfunction(),times=n) #run your function "n" times

Here is an example using rbenchmark:

rbenchmark::benchmark(myfunction(),replications=n) #run your function "n" times

For both packages you can get the result using operator <-. For example:

microbenchmark::microbenchmark(a<-myfunction(),times=n) # result is in variable "a"

rbenchmark::rbenchmark(a<-myfunction(),times=n) # result is in variable "a"

answered Nov 21 at 19:48

Csd

29819

add a comment |

up vote
0
down vote

You can use package microbenchmark or rbenchmark to test code.

First define a function:

myfunction <- function(){}

then define how many times should run the function

n <- 10

Here is an example using microbenchmark:

microbenchmark::microbenchmark(myfunction(),times=n) #run your function "n" times

Here is an example using rbenchmark:

rbenchmark::benchmark(myfunction(),replications=n) #run your function "n" times

For both packages you can get the result using operator <-. For example:

microbenchmark::microbenchmark(a<-myfunction(),times=n) # result is in variable "a"

rbenchmark::rbenchmark(a<-myfunction(),times=n) # result is in variable "a"

answered Nov 21 at 19:48

Csd

29819

add a comment |

up vote
0
down vote

You can use package microbenchmark or rbenchmark to test code.

First define a function:

myfunction <- function(){}

then define how many times should run the function

n <- 10

Here is an example using microbenchmark:

microbenchmark::microbenchmark(myfunction(),times=n) #run your function "n" times

Here is an example using rbenchmark:

rbenchmark::benchmark(myfunction(),replications=n) #run your function "n" times

For both packages you can get the result using operator <-. For example:

microbenchmark::microbenchmark(a<-myfunction(),times=n) # result is in variable "a"

rbenchmark::rbenchmark(a<-myfunction(),times=n) # result is in variable "a"

answered Nov 21 at 19:48

Csd

29819

You can use package microbenchmark or rbenchmark to test code.

First define a function:

myfunction <- function(){}

then define how many times should run the function

n <- 10

Here is an example using microbenchmark:

microbenchmark::microbenchmark(myfunction(),times=n) #run your function "n" times

Here is an example using rbenchmark:

rbenchmark::benchmark(myfunction(),replications=n) #run your function "n" times

For both packages you can get the result using operator <-. For example:

microbenchmark::microbenchmark(a<-myfunction(),times=n) # result is in variable "a"

rbenchmark::rbenchmark(a<-myfunction(),times=n) # result is in variable "a"

answered Nov 21 at 19:48

Csd

29819

answered Nov 21 at 19:48

Csd

29819

answered Nov 21 at 19:48

Csd

29819

answered Nov 21 at 19:48

Csd

29819

add a comment |

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