What does it mean when people say a cost function is something you want to minimize? Announcing the arrival of Valued Associate #679: Cesar Manara Planned maintenance scheduled April 23, 2019 at 23:30 UTC (7:30pm US/Eastern) 2019 Moderator Election Q&A - Questionnaire 2019 Community Moderator Election ResultsWhat does 'contextual' mean in 'contextual bandits'?What does “linear in parameters” mean?Linear regression - LMS with gradient descent vs normal equationsWhat does “zero-meaned vector” meanBest way to normalize datasets for a linear regression model?What does it mean when we say most of the points in a hypercube are at the boundary?What does backpropagating through labels mean?What causes the Shape (convex or non-convex) of the cost function?What does “Model recursive loss convergence” mean?What does the “Loss” value given by Keras mean?
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What does it mean when people say a cost function is something you want to minimize?
Announcing the arrival of Valued Associate #679: Cesar Manara
Planned maintenance scheduled April 23, 2019 at 23:30 UTC (7:30pm US/Eastern)
2019 Moderator Election Q&A - Questionnaire
2019 Community Moderator Election ResultsWhat does 'contextual' mean in 'contextual bandits'?What does “linear in parameters” mean?Linear regression - LMS with gradient descent vs normal equationsWhat does “zero-meaned vector” meanBest way to normalize datasets for a linear regression model?What does it mean when we say most of the points in a hypercube are at the boundary?What does backpropagating through labels mean?What causes the Shape (convex or non-convex) of the cost function?What does “Model recursive loss convergence” mean?What does the “Loss” value given by Keras mean?
$begingroup$
I am having a lot of trouble understanding this. Does it mean you should not use the cost function very often?
machine-learning beginner linear-regression
asked Jun 26 '16 at 8:05
jame_smithjame_smith
384
$endgroup$
add a comment |
$begingroup$
I am having a lot of trouble understanding this. Does it mean you should not use the cost function very often?
machine-learning beginner linear-regression
asked Jun 26 '16 at 8:05
jame_smithjame_smith
384
$endgroup$
add a comment |
$begingroup$
I am having a lot of trouble understanding this. Does it mean you should not use the cost function very often?
machine-learning beginner linear-regression
asked Jun 26 '16 at 8:05
jame_smithjame_smith
384
$endgroup$
I am having a lot of trouble understanding this. Does it mean you should not use the cost function very often?
machine-learning beginner linear-regression
machine-learning beginner linear-regression
asked Jun 26 '16 at 8:05
jame_smithjame_smith
384
asked Jun 26 '16 at 8:05
jame_smithjame_smith
384
asked Jun 26 '16 at 8:05
jame_smithjame_smith
384
asked Jun 26 '16 at 8:05
jame_smithjame_smith
384
asked Jun 26 '16 at 8:05
jame_smithjame_smith
384
384
add a comment |
add a comment |
5 Answers
5
active
oldest
votes
$begingroup$
No, it means you are trying to find the inputs that make the output of the cost function the smallest. It doesn't mean that you should "minimize" use of it.
answered Jun 26 '16 at 8:59
Sean OwenSean Owen
4,26642238
$endgroup$
$begingroup$
Lol.... thx for clearing out this confusion. :)
$endgroup$
– jame_smith
Jun 26 '16 at 9:44
add a comment |
$begingroup$
A cost function is something you use to penalize high deviations from the expected results when compared to your actual predictions.
You can think of a cost function as a sign of how bad your prediction was. A high cost function value means the prediction was really off, hence, the focus on minimizing the cost function, thereby producing an accurate prediction model.
answered Jun 26 '16 at 14:27
Vineet JohnVineet John
314
$endgroup$
add a comment |
$begingroup$
Cost functions in the context of Machine Learning often calculate some kind of metric that signifies how well your model is performing. A common one is for example the mean squared error, where you look at all your test examples where you know the true value and the predicted, take the difference between that and square it. By minimizing this error (cost function) you assume your predictions will be better.
answered Jun 26 '16 at 11:01
Jan van der VegtJan van der Vegt
6,7101839
$endgroup$
add a comment |
$begingroup$
Consider you have some data and you want to model a function that fits the data. This function should fit well and should not have error (ideally). How do I define this error? and voila here comes the cost function.
answered Jun 27 '16 at 12:05
Krishna KalyanKrishna Kalyan
15410
$endgroup$
add a comment |
$begingroup$
Minimize a (cost) function means that you want to find good values for its parameters. Good parameters means that the function can produce the best possible outcomes, namely the smallest ones, because small values mean less errors. This is an optimization problem: the problem of finding the best solution from all possible solutions. (source)
answered Jun 30 '16 at 7:31
IgnorantIgnorant
1012
$endgroup$
add a comment |
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5 Answers
5
active
oldest
votes
5 Answers
5
active
oldest
votes
active
oldest
votes
active
oldest
votes
$begingroup$
No, it means you are trying to find the inputs that make the output of the cost function the smallest. It doesn't mean that you should "minimize" use of it.
answered Jun 26 '16 at 8:59
Sean OwenSean Owen
4,26642238
$endgroup$
$begingroup$
Lol.... thx for clearing out this confusion. :)
$endgroup$
– jame_smith
Jun 26 '16 at 9:44
add a comment |
$begingroup$
No, it means you are trying to find the inputs that make the output of the cost function the smallest. It doesn't mean that you should "minimize" use of it.
answered Jun 26 '16 at 8:59
Sean OwenSean Owen
4,26642238
$endgroup$
$begingroup$
Lol.... thx for clearing out this confusion. :)
$endgroup$
– jame_smith
Jun 26 '16 at 9:44
add a comment |
$begingroup$
No, it means you are trying to find the inputs that make the output of the cost function the smallest. It doesn't mean that you should "minimize" use of it.
answered Jun 26 '16 at 8:59
Sean OwenSean Owen
4,26642238
$endgroup$
No, it means you are trying to find the inputs that make the output of the cost function the smallest. It doesn't mean that you should "minimize" use of it.
answered Jun 26 '16 at 8:59
Sean OwenSean Owen
4,26642238
edited Apr 4 at 15:59
answered Jun 26 '16 at 8:59
Sean OwenSean Owen
4,26642238
answered Jun 26 '16 at 8:59
Sean OwenSean Owen
4,26642238
answered Jun 26 '16 at 8:59
Sean OwenSean Owen
4,26642238
4,26642238
$begingroup$
Lol.... thx for clearing out this confusion. :)
$endgroup$
– jame_smith
Jun 26 '16 at 9:44
add a comment |
$begingroup$
Lol.... thx for clearing out this confusion. :)
$endgroup$
– jame_smith
Jun 26 '16 at 9:44
$begingroup$
Lol.... thx for clearing out this confusion. :)
$endgroup$
– jame_smith
Jun 26 '16 at 9:44
$begingroup$
Lol.... thx for clearing out this confusion. :)
$endgroup$
– jame_smith
Jun 26 '16 at 9:44
add a comment |
$begingroup$
A cost function is something you use to penalize high deviations from the expected results when compared to your actual predictions.
You can think of a cost function as a sign of how bad your prediction was. A high cost function value means the prediction was really off, hence, the focus on minimizing the cost function, thereby producing an accurate prediction model.
answered Jun 26 '16 at 14:27
Vineet JohnVineet John
314
$endgroup$
add a comment |
$begingroup$
A cost function is something you use to penalize high deviations from the expected results when compared to your actual predictions.
You can think of a cost function as a sign of how bad your prediction was. A high cost function value means the prediction was really off, hence, the focus on minimizing the cost function, thereby producing an accurate prediction model.
answered Jun 26 '16 at 14:27
Vineet JohnVineet John
314
$endgroup$
add a comment |
$begingroup$
A cost function is something you use to penalize high deviations from the expected results when compared to your actual predictions.
You can think of a cost function as a sign of how bad your prediction was. A high cost function value means the prediction was really off, hence, the focus on minimizing the cost function, thereby producing an accurate prediction model.
answered Jun 26 '16 at 14:27
Vineet JohnVineet John
314
$endgroup$
A cost function is something you use to penalize high deviations from the expected results when compared to your actual predictions.
You can think of a cost function as a sign of how bad your prediction was. A high cost function value means the prediction was really off, hence, the focus on minimizing the cost function, thereby producing an accurate prediction model.
answered Jun 26 '16 at 14:27
Vineet JohnVineet John
314
answered Jun 26 '16 at 14:27
Vineet JohnVineet John
314
answered Jun 26 '16 at 14:27
Vineet JohnVineet John
314
answered Jun 26 '16 at 14:27
Vineet JohnVineet John
314
314
add a comment |
add a comment |
$begingroup$
Cost functions in the context of Machine Learning often calculate some kind of metric that signifies how well your model is performing. A common one is for example the mean squared error, where you look at all your test examples where you know the true value and the predicted, take the difference between that and square it. By minimizing this error (cost function) you assume your predictions will be better.
answered Jun 26 '16 at 11:01
Jan van der VegtJan van der Vegt
6,7101839
$endgroup$
add a comment |
$begingroup$
Cost functions in the context of Machine Learning often calculate some kind of metric that signifies how well your model is performing. A common one is for example the mean squared error, where you look at all your test examples where you know the true value and the predicted, take the difference between that and square it. By minimizing this error (cost function) you assume your predictions will be better.
answered Jun 26 '16 at 11:01
Jan van der VegtJan van der Vegt
6,7101839
$endgroup$
add a comment |
$begingroup$
Cost functions in the context of Machine Learning often calculate some kind of metric that signifies how well your model is performing. A common one is for example the mean squared error, where you look at all your test examples where you know the true value and the predicted, take the difference between that and square it. By minimizing this error (cost function) you assume your predictions will be better.
answered Jun 26 '16 at 11:01
Jan van der VegtJan van der Vegt
6,7101839
$endgroup$
Cost functions in the context of Machine Learning often calculate some kind of metric that signifies how well your model is performing. A common one is for example the mean squared error, where you look at all your test examples where you know the true value and the predicted, take the difference between that and square it. By minimizing this error (cost function) you assume your predictions will be better.
answered Jun 26 '16 at 11:01
Jan van der VegtJan van der Vegt
6,7101839
answered Jun 26 '16 at 11:01
Jan van der VegtJan van der Vegt
6,7101839
answered Jun 26 '16 at 11:01
Jan van der VegtJan van der Vegt
6,7101839
answered Jun 26 '16 at 11:01
Jan van der VegtJan van der Vegt
6,7101839
6,7101839
add a comment |
add a comment |
$begingroup$
Consider you have some data and you want to model a function that fits the data. This function should fit well and should not have error (ideally). How do I define this error? and voila here comes the cost function.
answered Jun 27 '16 at 12:05
Krishna KalyanKrishna Kalyan
15410
$endgroup$
add a comment |
$begingroup$
Consider you have some data and you want to model a function that fits the data. This function should fit well and should not have error (ideally). How do I define this error? and voila here comes the cost function.
answered Jun 27 '16 at 12:05
Krishna KalyanKrishna Kalyan
15410
$endgroup$
add a comment |
$begingroup$
Consider you have some data and you want to model a function that fits the data. This function should fit well and should not have error (ideally). How do I define this error? and voila here comes the cost function.
answered Jun 27 '16 at 12:05
Krishna KalyanKrishna Kalyan
15410
$endgroup$
Consider you have some data and you want to model a function that fits the data. This function should fit well and should not have error (ideally). How do I define this error? and voila here comes the cost function.
answered Jun 27 '16 at 12:05
Krishna KalyanKrishna Kalyan
15410
answered Jun 27 '16 at 12:05
Krishna KalyanKrishna Kalyan
15410
answered Jun 27 '16 at 12:05
Krishna KalyanKrishna Kalyan
15410
answered Jun 27 '16 at 12:05
Krishna KalyanKrishna Kalyan
15410
15410
add a comment |
add a comment |
$begingroup$
Minimize a (cost) function means that you want to find good values for its parameters. Good parameters means that the function can produce the best possible outcomes, namely the smallest ones, because small values mean less errors. This is an optimization problem: the problem of finding the best solution from all possible solutions. (source)
answered Jun 30 '16 at 7:31
IgnorantIgnorant
1012
$endgroup$
add a comment |
$begingroup$
Minimize a (cost) function means that you want to find good values for its parameters. Good parameters means that the function can produce the best possible outcomes, namely the smallest ones, because small values mean less errors. This is an optimization problem: the problem of finding the best solution from all possible solutions. (source)
answered Jun 30 '16 at 7:31
IgnorantIgnorant
1012
$endgroup$
add a comment |
$begingroup$
Minimize a (cost) function means that you want to find good values for its parameters. Good parameters means that the function can produce the best possible outcomes, namely the smallest ones, because small values mean less errors. This is an optimization problem: the problem of finding the best solution from all possible solutions. (source)
answered Jun 30 '16 at 7:31
IgnorantIgnorant
1012
$endgroup$
Minimize a (cost) function means that you want to find good values for its parameters. Good parameters means that the function can produce the best possible outcomes, namely the smallest ones, because small values mean less errors. This is an optimization problem: the problem of finding the best solution from all possible solutions. (source)
answered Jun 30 '16 at 7:31
IgnorantIgnorant
1012
answered Jun 30 '16 at 7:31
IgnorantIgnorant
1012
answered Jun 30 '16 at 7:31
IgnorantIgnorant
1012
answered Jun 30 '16 at 7:31
IgnorantIgnorant
1012
1012
add a comment |
add a comment |
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