Regression Model for explained model(Details inside)

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Mike
Mike el 16 de Oct. de 2014
Respondida: Hari el 4 de Feb. de 2025
I am kind of a newbie on machine learning and I would like to ask some questions based on a problem I have .
Let's say I have x y z as variable and I have values of these variables as time progresses like :
  • t0 = x0 y0 z0
  • t1 = x1 y1 z1
  • tn = xn yn zn
Now I want a model that when it's given 3 values of x , y , z I want a prediction of them like:
  • Input : x_test y_test z_test
  • Output : x_prediction y_prediction z_prediction
These values are float numbers. What is the best model for this kind of problem? Thanks in advance for all the answers.

Respuestas (1)

Hari
Hari el 4 de Feb. de 2025
Hi Mike,
I understand that you want to develop a machine learning model that can predict future values of three variables (x, y, z) based on their historical values over time.
  1. Given that you have time-series data for the variables x, y, and z, a suitable approach would be to use time-series forecasting models. These models can capture temporal dependencies and trends in the data.
  2. A common and effective method for time-series prediction is using Recurrent Neural Networks (RNNs), particularly Long Short-Term Memory (LSTM) networks. LSTMs are well-suited for capturing long-term dependencies in sequential data.
  3. Another approach could be to use a multivariate linear regression model if the relationship between the variables and time is linear. This model can predict future values based on past observations.
  4. For non-linear relationships, you might consider using a more complex model like a Random Forest or a Gradient Boosting Machine, which can handle non-linear interactions between variables.
  5. If you have sufficient data and computational resources, you could also explore using deep learning models like Convolutional Neural Networks (CNNs) for time-series data, which can capture spatial dependencies.
Refer to the documentation of Deep Learning Toolbox for more details on implementing LSTM networks: https://www.mathworks.com/help/deeplearning/ug/long-short-term-memory-networks.html
Refer to the documentation of Statistics and Machine Learning Toolbox for regression models: https://www.mathworks.com/help/stats/regression-learner-app.html
Hope this helps!

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