will it work for multivariate time series prediction both regression and classification

[Sandy4321]

great code thanks may you clarify : will it work for multivariate time series prediction both regression and classification 1 where all values are continues values 2 or even will it work for multivariate time series where values are mixture of continues and categorical values for example 2 dimensions have continues values and 3 dimensions are categorical values

color        weight     gender  height  age  

1 black 56 m 160 34 2 white 77 f 170 54 3 yellow 87 m 167 43 4 white 55 m 198 72 5 white 88 f 176 32

[dmbee]

will it work for multivariate time series prediction both regression and classification: yes where all values are continues values: yes where values are mixture of continues and categorical values: yes

For the last one - you'll need to encode the categorical variables as a number (eg m = 0.0, f = 1.0). Note you can use different features (if you're using engineered feature approach) for different variables with FeatureRepMix, so you can also treat these variables differently that way if you wish.

[Sandy4321]

great do you have code example for "where values are mixture of continues and categorical values: yes"

[dmbee]

see the examples in the docs eg https://dmbee.github.io/seglearn/auto_examples/plot_feature_rep.html#sphx-glr-auto-examples-plot-feature-rep-py