Preparing data for Classification Learner
2 ビュー (過去 30 日間)
古いコメントを表示
I have received a file with data for classification. The structure of file is such that there are around 70 structures. Each structure consists of s1 and s5 matrices, each of approximately 300 x 320 numerical readings and a label (0/1).
There is no additional information about the data, and there are no other labels. As far as I understand this, S1 should be training data, while s5 should be test data.
I have struck a wall in preparing this for a Classification learner, and I was not able to transform data into appropriate form to match each matrix to each label, that is to correctly import data into CL app. I am failing to see how to do this transformation, and if I might be missing a step here.
I would greatly appreciate any help with this.
Thank you
1 件のコメント
Ahmet Cecen
2015 年 4 月 22 日
編集済み: Ahmet Cecen
2015 年 4 月 22 日
There are a lot of holes in this story, at least for me, to be able to help you. I can inspect the data if you share it and see if I can help you, since there is no additional information about the data apparently.
回答 (2 件)
HUGO SILVA
2017 年 8 月 4 日
I would like to know more how to prepare data for Classification Learner.
I am starter and I am having some difficults to use the app Classifation Learner. I am trying to find a video, or a detailed tutorial that teach how to prepare data, but I don't find it.
I have datas where a I would like classified 4 kinds of peaks. I am have difficult to create a file, or table, where it has datas and response wished.
How can I do it?
0 件のコメント
Mubashir
2017 年 8 月 18 日
firstly prepare single data file in form of table or matrix. Using workspace import data in Classification learner. Then assign predictor or response to specified variables and then go further to select your further classification techniques.
0 件のコメント
参考
カテゴリ
Help Center および File Exchange で Classification Learner App についてさらに検索
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!