Question

我会在两个密集向量之间进行减法，它们都是数据集和函数的结果。有一个例子

1. The first dense vector is a row of dataset(*, 2)

BroadcastedRows(DenseVector(0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 1.0, 1.0, 1.0))

2. The second dense vector is a return of predict_coef_sgd(dataset, coef)

DenseVector(0.2987569855650975,  0.14595105593031163, 0.08533326519733725,
            0.21973731424800344, 0.24705900008926596, 0.9547021347460022, 
            0.8620341905282771,  0.9717729050420985,  0.9992954520878627, 
            0.9054893228110497)

我减去它时出错了

dataset(*, 2) - predict_coef_sgd(dataset, coef)

Name: Compile Error
Message: <console>:36: error: could not find implicit value for parameter op: breeze.linalg.operators.OpSub.Impl2[breeze.linalg.BroadcastedRows[breeze.linalg.DenseVector[Double],breeze.linalg.DenseVector[Double]],breeze.linalg.DenseVector[Double],That]
       dataset(*, 2) - predict_coef_sgd(dataset, coef)
                     ^
StackTrace:

请评论如何转换＆＃34; BroadcastedRows（DenseVector＆＃34;到密集的矢量。谢谢。

Answer 1

根据约翰的评论，提到row-broadcasting and transposed vectors?它解决了，然而，我不明白为什么，如果你能详细解释，请随时评论

(dataset.t(2,::) - predict_coef_sgd(dataset, coef).t).t

DenseVector(-0.2987569855650975, -0.14595105593031163, -0.08533326519733725,
            -0.21973731424800344, -0.24705900008926596, 0.045297865253997815,
             0.13796580947172288, 0.028227094957901544, 7.045479121372544E-4, 
             0.09451067718895034)

如何在微风中使用BroadcastedRows进行减法

1 个答案: