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Data Science

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  • $\begingroup$ I am not using a neural network. The data is set simple, though it has a lot of categorical features so neural network might consume a lot of memory unnecessarily. Any other way that I can follow? $\endgroup$ Commented Jan 24, 2020 at 16:05
  • $\begingroup$ You can still normalize it channelwise if each feature has different range and all. Like year of birth would be in the range of 1900-2000s, body weight would be in a different range. You can use this new data for clustering and it should give better results. You can also prune out less probable data points from the dataset, if you are sure of it. This can also be used to tackle (possible) class imbalance. If you can describe the kind of classification that you expect to do, maybe we can discuss more. $\endgroup$ Commented Jan 24, 2020 at 16:19