How to do basic linear prediction with Classification Learner?

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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?

Answers (1)

Uttiya Ghosh
Uttiya Ghosh on 15 Jul 2020
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.

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