Mysql多变量线性回归

发布于 2024-08-18 16:45:46 字数 704 浏览 4 评论 0原文

我正在尝试对 mysql 5.0 数据库中的数据进行多变量（9 个变量）线性回归（结果值字段只有 2 个可能的值，1 和 0）。

我做了一些搜索，发现我可以使用：

mysql> SELECT
    -> @n := COUNT(score) AS N,
    -> @meanX := AVG(age) AS "X mean",
    -> @sumX := SUM(age) AS "X sum",
    -> @sumXX := SUM(age*age) "X sum of squares",
    -> @meanY := AVG(score) AS "Y mean",
    -> @sumY := SUM(score) AS "Y sum",
    -> @sumYY := SUM(score*score) "Y sum of square",
    -> @sumXY := SUM(age*score) AS "X*Y sum"

来获取许多基本回归变量，但我真的不想为 9 个变量的每个组合键入此操作。我能找到的有关如何对多变量进行回归的所有资源都需要矩阵运算。我可以使用mysql进行矩阵运算，还是有其他方法可以进行9变量线性回归？

我应该先将数据导出mysql吗？它大约有 80,000 行，所以移动它就可以了，只是不确定我还应该使用什么。

谢谢，担

原文

I am trying to do a multivarible (9 variables) linear regression on data in my mysql 5.0 database (the result value field only has 2 possible values, 1 and 0).

I've done some searching and found I can use:

mysql> SELECT
    -> @n := COUNT(score) AS N,
    -> @meanX := AVG(age) AS "X mean",
    -> @sumX := SUM(age) AS "X sum",
    -> @sumXX := SUM(age*age) "X sum of squares",
    -> @meanY := AVG(score) AS "Y mean",
    -> @sumY := SUM(score) AS "Y sum",
    -> @sumYY := SUM(score*score) "Y sum of square",
    -> @sumXY := SUM(age*score) AS "X*Y sum"

To get at many of the basic regression variables, but I really don't want to type out doing this for every combination of the 9 variables. All of the sources I can find about how to do regression on multi variables requires Matrix operations. Can I do Matrix operations with mysql, or are there other ways to do a 9 variable linear regression?

Should I export the data out of mysql first? Its ~80,000 rows, so it would be alright to move it, just not sure what else I should use.

Thanks,
Dan

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傲世九天 2024-08-25 16:45:46

最好将这些数据存储在 MySQL 中，但您可以使用能够访问数据库的语言来处理数据。伪代码：

variables = [ 'A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I' ];

for X in $variables do
    for Y in $variables do
        query = 'SELECT
            @'+$X+$Y+' := COUNT(score) AS '+$X+$Y+',
            @mean'+$X+' := AVG(age) AS "X mean",
            @sum'+$X+' := SUM(age) AS "X sum",
            @sum'+$X+$X+' := SUM(age*age) "X sum of squares",
            @mean'+$Y+' := AVG(score) AS "Y mean",
            @sum'+$Y+' := SUM(score) AS "Y sum",
            @sum'+$Y+$Y+' := SUM(score*score) "Y sum of square",
            @sum'+$X+$Y+' := SUM(age*score) AS "X*Y sum"';
        db_execute(query);
    done
done

但为什么不将结果存储在表中？更适合数据库。

for X in $variables do
    for Y in $variables do
        query = 'INSERT INTO regression SELECT FROM measurements
            "'+$X+'" AS X
            "'+$Y+'" AS Y
            score AS valX
            age AS valY
            COUNT(score) AS N,
            AVG(age) AS meanX,
            SUM(age) AS sumX,
            SUM(age*age) squareX,
            AVG(score) AS meanY,
            SUM(score) AS sumY,
            SUM(score*score) squareY,
            SUM(age*score) AS sumXY';
        db_execute(query);
    done
done

在 X 列和 Y 列上放置单独的索引。

It is good to store this data in MySQL but you could process the data from a language that has access to the database. Pseudocode:

variables = [ 'A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I' ];

for X in $variables do
    for Y in $variables do
        query = 'SELECT
            @'+$X+$Y+' := COUNT(score) AS '+$X+$Y+',
            @mean'+$X+' := AVG(age) AS "X mean",
            @sum'+$X+' := SUM(age) AS "X sum",
            @sum'+$X+$X+' := SUM(age*age) "X sum of squares",
            @mean'+$Y+' := AVG(score) AS "Y mean",
            @sum'+$Y+' := SUM(score) AS "Y sum",
            @sum'+$Y+$Y+' := SUM(score*score) "Y sum of square",
            @sum'+$X+$Y+' := SUM(age*score) AS "X*Y sum"';
        db_execute(query);
    done
done

but why do not store the results in a table? More appropriate for a database.

for X in $variables do
    for Y in $variables do
        query = 'INSERT INTO regression SELECT FROM measurements
            "'+$X+'" AS X
            "'+$Y+'" AS Y
            score AS valX
            age AS valY
            COUNT(score) AS N,
            AVG(age) AS meanX,
            SUM(age) AS sumX,
            SUM(age*age) squareX,
            AVG(score) AS meanY,
            SUM(score) AS sumY,
            SUM(score*score) squareY,
            SUM(age*score) AS sumXY';
        db_execute(query);
    done
done

Put separate index on both X and the Y columns.

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