# What is the best training method for 15-30k records with 5-12 features to classify data into 2 groups?

I don't know if this is a suitable question here. I have data from 2 groups, neutral and positive.

Here how the data looks like

A   02.840  00.960  00.950  00.995  00.995  00.602  1
B   04.730  01.000  01.000  00.999  01.000  01.000  1
C   NULL    00.970  00.005  00.078  00.987  00.000  0
D   NULL    01.000  01.000  00.010  00.675  00.451  1
E   00.530  01.000  00.022  00.231  00.443  00.000  0


The first column is the record name/ID and the last column is its class/group. The six columns in the middle are the features which some of them might be NULL.

With the knowledge that I studied years ago, I'm gonna try ANN and SVM first. But I'm not sure if I am on the right track. So I wonder if anyone here can guide me.

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