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Classification technique to classify categories in two variables when dateset has larger number of numerical variables and few data points

Cross Validated Asked by rbeginner on November 12, 2021

I’m doing data analysis and need to build a classification model.

Data set has 72 data points and

  1. 37 numerical variables
  2. Two categorical variables

categorical variable 1 has two levels A and B
categorical variable 2 has 4 levels W, X, Y and Z

What I have tried so far?

I couldn’t figure out how to build a two-step classification model. I could only classify into one categorical variable at once.

  1. Logistic regression model for categorical variable 2

Did a PCA on 80% of training data and used the first 5 PCs (explained about 95% of variation). Then tested on the remaining 20%. had an accuracy of about 75%. I did 5 fold cross-validation

  1. tried K nearest neighbor, Support vector machines, neuralnet in r (due to small number of data kicked this method)

What I need advice about?

Classification model to classify a data point into categorical variable 1 (Level A or B) and categorical variable 2 (Level W, X, Y, and Z) using r software.

I need a model that would do the classification into both variables at once if possible. Any direction or guidance is appreciated.

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