Dear @Jaber_Al_Nahian thanks for the question and welcome to neurostars!
1—You can specify the classification algorithm in the cfnParams structure. You can see the options in GiveMeCfn. Typically because there is complexity in the embedding in a high-dimensional feature space, we have tried to remove complexity in the classifiers (to avoid overfitting), also for interpretability. You can also use OutputToCSV and use the hctsa data in other environments (like python), [if this route, feel free to share your python workflow here]
2—hctsa is designed to extracting features from a univariate time series. We are currently designing and implementing a multivariate version. In the meantime, you can either concatenate univariate features of each component of your system (e.g., using a reduced set of features, like catch22 to avoid massive dimensionality explosion), and perhaps add some simple pairwise dependence measures to summarize the multivariate structure.
3—Can you confirm what toolboxes you have (and what Matlab version you’re using)? If you have Matlab2020 it tries to use confusionchart, and otherwise tries to use plotconfusion (requires the Deep Learning toolbox). See lines 214–222 of TS_Classify.
4—Use OutputToCSV—gives you csv files corresponding to a given HCTSA calculation that you can analyze however you please.
Hope this helps, and good luck!
Ben