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The appliance of MLPs to sequence prediction demands which the input sequence be divided into smaller overlapping subsequences termed Home windows which can be shown on the network to be able to produce a prediction.
or please recommend me A few other process for such a find out dataset (ISCX -2012) during which focus on class is categorical and all other attributes are continuous.
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Create a design on Each individual list of attributes and Review the effectiveness of each and every. Look at ensembling the products together to determine if efficiency could be lifted.
I have a dataset which is made up of the two categorical and numerical characteristics. Should I do feature assortment in advance of one particular-sizzling encoding of categorical functions or following that ?