Data Division of Neural Network training?

7 次查看（过去 30 天）
Ali Almakhmari
Ali Almakhmari 2023-8-18
回答： Shreeya 2023-8-22
I have a 2000000 by 7 matrix where the first 6 volumns are inputs and the last column is the output. So I am training a neural network to fit the 7th column as a function of the first 6 columns:
Input=Input;
Output=Output;
ANN=fitnet([25],'trainbr');
ANN=train(ANN,Input,Output);
My problem is the data division. Since the data is divided into three section: validation, test, and training. I want to make sure that the last 100 rows (index: 1999900 to 2000000) are included in the training set, and the rest of the data (rows) are randomized into the three sections. "dividerand" does what I want but unfortunately, it does not gurantee that the last 100 rows are in the training set. Do you guys have any solutions?
  4 个评论
显示 2更早的评论
NAVNEET NAYAN
NAVNEET NAYAN 2023-8-18
编辑：NAVNEET NAYAN 2023-8-18
What I am saying is remove the last 100 rows and use "dividerand" on the rest of the data.
Ali Almakhmari
Ali Almakhmari 2023-8-18
ahhh...how will this ensure that the 100 rows are in the training section?

请先登录，再进行评论。

请先登录，再回答此问题。

采纳的回答

Shreeya
Shreeya 2023-8-22
Hello Ali Almakhmari
To ensure that the last 100 rows are included in the training set, you can split the data into two arrays, the first set having data from index 0 to 1999900 and the second one should contain data from 1999900 to 2000000. Then, you can use the “dividerand" function to split the first array into training, testing and validation datasets.
After that you can concatenate the training dataset obtained from splitting the first array with the last 100 rows to create the desired input features dataset.
Hope this helps!

更多回答（0 个）

类别

在 Help Center 和 File Exchange 中查找有关 Sequence and Numeric Feature Data Workflows 的更多信息

标签

产品


版本

R2022b

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by