How to do basic linear prediction with Classification Learner?

I did really basic operation with Classification Learner. I defined a 4x2 matrix and first column is my input [1;2;3;4], second is my output [2;4;6;8]. I trained this with Classificaiton Learner. I got 100% at SVM model. Then i tried new data x=[5;6;7;8] with this trained model then i got y=[8;8;8;2]. But i supposed to get y=[10;12;14;16]. Why this error occured? Can Classification do such things? Can anyone help me? What is the right code?

Answer 1

[Uttiya Ghosh]

Hi Tayfun,

As per my understanding you would like to predict a continuous target feature using continuous numeric features. A classification model works well for situations where the target feature is discrete in nature. A regression model on the other hands predicts a continuous target feature. PFB the code of a linear regression model that can be used to achieve your task.

mdl = fitlm ([1;2;3;4],[2;4;6;8]);
pred = predict(mdl,[5;6;7;8]);

For more information, refer to the following link.

https://www.mathworks.com/help/stats/linear-regression-model-workflow.html