Multivariate non-time series
Posted: Wed Feb 15, 2023 07:04
Similar to this previous question: (http://forum.recurrence-plot.tk/viewtop ... f=4&t=3591).
I'd like to take multivariate data (independent feature1, feature2, ..., featureN) and convert each row into an image for classification. There are perhaps 10 features as well as a dependent variable, while the dependent variable is kept out of the image. A post elsewhere online suggested using recurrence plots to convert the row into an image. I tried doing this with the data (see attachment) using for example this Python library (https://github.com/laszukdawid/recurrence-plot).
A sample row of the dataset looks like this, where the exceedance column holds the dependent variable:
I'd like to take multivariate data (independent feature1, feature2, ..., featureN) and convert each row into an image for classification. There are perhaps 10 features as well as a dependent variable, while the dependent variable is kept out of the image. A post elsewhere online suggested using recurrence plots to convert the row into an image. I tried doing this with the data (see attachment) using for example this Python library (https://github.com/laszukdawid/recurrence-plot).
A sample row of the dataset looks like this, where the exceedance column holds the dependent variable:
Exceedance is a binary variable (0 or 1). My plan is to use existing image classification approaches to classify the images. Does the use of recurrence plots in this case appear valid? Is this approach too far out? Perhaps another multivariate-to-image approach is warranted?year month day dayofyear tide tide_gtm dtide_1 dtide_2 PrecipSum6 Precip24 lograin3T wet3 lograin7T wet7 Wtemp_B rad solar_noon WDIR WSPD awind owind exceedance
2016 6 1 153 176.91 1.00 -0.01 -0.09 0.00 0.00 -1.52 0.00 0.35 1.00 19.90 0.00 1.00 0.00 0.00 -0.00 0.00 1