optimization problem to filter samples
$begingroup$
I am trying to find the right algorithm (or topic to study) to optimize this problem, if anyone knows an algorithm that can help please let me know.
I have a data set $S$ of $N$ samples, $S=${$A_1,A_2,...,A_N$}.
Each sample, $A_i$, has 2 variables, $vec{x}$ and z, where
$z=f(vec{x})$, and $vec{x}=x_1,x_2,...,x_n$.
$vec{x_i}$ is a vector that contains information about each sample $A_i$.
Let $n$ be the number of samples in a subset of S. Then $Z := frac{sum_1^n z}{n}$, is the average of each $z_i$ in the subset.
I want to maximize $Z*n$, and I also want to find max{$Z$} independent of $n$.
Right now I think of the $x$'s like filters. If I take the subset $s_1=${$A_i : x_1in[20.05,30] cup [-30,-20.05], A_iin S$} I get a particular subset of $S$ of cardinality $n_i$.
Also, each variable $x_i$ has some number above or below which $nrightarrow 0$
Basically I think optimizing this problem means I have to find $a,b$ such that I get the maximum $n * Z$ when I apply the filter $a<x_i<b$.
Anyone have any idea how to optimize it? I tried brute force, but way too many operations.
optimization
$endgroup$
add a comment |
$begingroup$
I am trying to find the right algorithm (or topic to study) to optimize this problem, if anyone knows an algorithm that can help please let me know.
I have a data set $S$ of $N$ samples, $S=${$A_1,A_2,...,A_N$}.
Each sample, $A_i$, has 2 variables, $vec{x}$ and z, where
$z=f(vec{x})$, and $vec{x}=x_1,x_2,...,x_n$.
$vec{x_i}$ is a vector that contains information about each sample $A_i$.
Let $n$ be the number of samples in a subset of S. Then $Z := frac{sum_1^n z}{n}$, is the average of each $z_i$ in the subset.
I want to maximize $Z*n$, and I also want to find max{$Z$} independent of $n$.
Right now I think of the $x$'s like filters. If I take the subset $s_1=${$A_i : x_1in[20.05,30] cup [-30,-20.05], A_iin S$} I get a particular subset of $S$ of cardinality $n_i$.
Also, each variable $x_i$ has some number above or below which $nrightarrow 0$
Basically I think optimizing this problem means I have to find $a,b$ such that I get the maximum $n * Z$ when I apply the filter $a<x_i<b$.
Anyone have any idea how to optimize it? I tried brute force, but way too many operations.
optimization
$endgroup$
add a comment |
$begingroup$
I am trying to find the right algorithm (or topic to study) to optimize this problem, if anyone knows an algorithm that can help please let me know.
I have a data set $S$ of $N$ samples, $S=${$A_1,A_2,...,A_N$}.
Each sample, $A_i$, has 2 variables, $vec{x}$ and z, where
$z=f(vec{x})$, and $vec{x}=x_1,x_2,...,x_n$.
$vec{x_i}$ is a vector that contains information about each sample $A_i$.
Let $n$ be the number of samples in a subset of S. Then $Z := frac{sum_1^n z}{n}$, is the average of each $z_i$ in the subset.
I want to maximize $Z*n$, and I also want to find max{$Z$} independent of $n$.
Right now I think of the $x$'s like filters. If I take the subset $s_1=${$A_i : x_1in[20.05,30] cup [-30,-20.05], A_iin S$} I get a particular subset of $S$ of cardinality $n_i$.
Also, each variable $x_i$ has some number above or below which $nrightarrow 0$
Basically I think optimizing this problem means I have to find $a,b$ such that I get the maximum $n * Z$ when I apply the filter $a<x_i<b$.
Anyone have any idea how to optimize it? I tried brute force, but way too many operations.
optimization
$endgroup$
I am trying to find the right algorithm (or topic to study) to optimize this problem, if anyone knows an algorithm that can help please let me know.
I have a data set $S$ of $N$ samples, $S=${$A_1,A_2,...,A_N$}.
Each sample, $A_i$, has 2 variables, $vec{x}$ and z, where
$z=f(vec{x})$, and $vec{x}=x_1,x_2,...,x_n$.
$vec{x_i}$ is a vector that contains information about each sample $A_i$.
Let $n$ be the number of samples in a subset of S. Then $Z := frac{sum_1^n z}{n}$, is the average of each $z_i$ in the subset.
I want to maximize $Z*n$, and I also want to find max{$Z$} independent of $n$.
Right now I think of the $x$'s like filters. If I take the subset $s_1=${$A_i : x_1in[20.05,30] cup [-30,-20.05], A_iin S$} I get a particular subset of $S$ of cardinality $n_i$.
Also, each variable $x_i$ has some number above or below which $nrightarrow 0$
Basically I think optimizing this problem means I have to find $a,b$ such that I get the maximum $n * Z$ when I apply the filter $a<x_i<b$.
Anyone have any idea how to optimize it? I tried brute force, but way too many operations.
optimization
optimization
asked Dec 1 '18 at 8:36
FrankFrank
16210
16210
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add a comment |
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