MATLAB: Multiple regression analysis, categorial variables, continuous variable

categorial variabledummyvarmultiple regression

Hi, I would like to run a multiple regression where my dependent variable is continuous. One of my independent variable is continuous, and the other independent variable is a category (small cap, midcap, largecap). I am not sure how to construct categorical independent variable. Do I have to use dummyvar function or can I just use 0 and 1 (1 for the category that applies to the observation).

Thank you in advance.

Best Answer

as long as you have one category variable, you can use just (0,1).

If , for example you had more than one category (small cap , mid cap, large cap); (public,private);(transportation,conglomerate,medical,etc) you would have to use dummyvar

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MATLAB: Train Categorial data in Neural Network Model

Hi,

Refer to the information below,

If the xlsx file provided in the question is the only data you are working on, you can use any classification algorithms available in Statistics and machine learning toolbox
If you are also working with sequence and time series data, I recommend you to use Long Short-Term Memory Networks. A Time series data contains set of observations on the values that a variable takes at different times.
If in case you are working with large data set along with attached xlsx file, I recommend you to use any neural network in MATLAB.

Hope this helps!

MATLAB: How to turn new dumthe variables into the same dumthe variables I used to create a model

There is no direct way to tell dummyvar to use a previously created dummyvar predictor matrix as a reference. So, in this case you would need to dummy-code each categorical variable separately and then do the same for the test vector. The following example should explain the workflow you would need to follow:

Say you have two categorical variables: Month, with categories, 1 to 12 and LeapYear with categories 0 and 1.

In this case, you would need to use the following code:

Monthcat = categorical(Month);
LeapYearcat = categorical(LeapYear);
dumMonth = dummyvar(Monthcat);
dumLeap = dummyvar(LeapYearcat);
dumPredictorMat = [dumMonth dumLeap]; % This would be the input to train your model
% Test inputs
MonthTest = 4;
LeapYearTest = 1;
% Separately dummy coding these inputs
MonthTestcat = categorical(MonthTest,1:12);
LeapTestcat = categorical(LeapYearTest,0:1);
%%Dummy coding them individually before using the model to predict
dumMonthTest = dummyvar(MonthTestcat);
dumLeapTest = dummyvar(LeapTestcat);
dummyTestMat = [dumMonthTest dumLeapTest];

Now you should be able to use the dummyTestMat as an input to the predict function of the model to generate the corresponding predicted responses.

Best Answer

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MATLAB: Train Categorial data in Neural Network Model

MATLAB: How to turn new dumthe variables into the same dumthe variables I used to create a model

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