Time Series Classification with a convolutional neural network ?
조회 수: 64 (최근 30일)
이전 댓글 표시
Hello Community,
my lack of experience in machine learning leads me to ask you guys. I want to classify different time series.
A bit background:
I measured the movement of my skateboard while doing tricks with an IMU ( gyroscope, accelerometer, magnetometer). I did 4 different tricks, each 50 times. Than i cute the long time series with all tricks in it into samples ( 1 sample is 1 trick each with the same lenght) and sorted by trick (class).
My goal would be, that I can show my machine data and it can classify by its class ( type of trick).
I read alot about this things and I think there are many ways to acchive this. I read that a convolutional neural network or a decision tree could be a good solution. What do you think - any suggestions ?
Would appreaciate all answers.
Have a good day!
댓글 수: 0
채택된 답변
Aditya Patil
2021년 7월 14일
As the data is temporal, you can use one of the sequence classification models. For example, you can use LSTMs (Long Short-Term Memory Networks). See the sequence classification using Deep Learning example https://www.mathworks.com/help/deeplearning/ug/classify-sequence-data-using-lstm-networks.html.
Alternately, if you know that the data can be represented well in structural format, you can use any of the classification algorithms/models available in Statistics and Machine Learning Toolbox, or in Deep Learning Toolbox.
I also recommend looking for pretrained models for this task and trying transfer learning.
댓글 수: 0
추가 답변 (0개)
참고 항목
카테고리
Help Center 및 File Exchange에서 Deep Learning Toolbox에 대해 자세히 알아보기
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!