forum.alglib.nethttp://forum.alglib.net/ Problem with random foresthttp://forum.alglib.net/viewtopic.php?f=2&t=3829 Page 1 of 1

 Author: antonysoldatov [ Wed Jan 03, 2018 1:07 pm ] Post subject: Problem with random forest Hello!I get problem with using random forest methodsHere is building RFCode:  double[,] xy = new double[,]  {{0, 0, 0, 0, 0, 255, 0, 0, 0},  {0, 0, 0, 0, 0, 0, 0, 0, 1},  {0, 255, 0, 0, 0, 0, 0, 0, 2},  {0, 0, 0, 0, 255, 0, 0, 0, 3},  {0, 0, 0, 0, 0, 0, 0, 255, 4}};  alglib.dfbuildrandomdecisionforestx1(xy, 8, 5, 5, 50, 3, 0.6, out info, out df, out rep);When I try to use it like this Code:double[] x = new double[]{0, 0, 0, 0, 0, 0, 0, 0};  alglib.dfprocess(df, x, ref y);I get wrong classification result {0.005, 0.49, 0, 0.505, 0}. So max possibility is 4th value (0.505). But it should be 2nd value (inner value is zero array, that is class 1)Please help me to solve this problem.Thank you!

 Author: Sergey.Bochkanov [ Wed Jan 03, 2018 4:59 pm ] Post subject: Re: Problem with random forest Hi!Random forests are (no surprise!) randomized constructs. They try randomly many different classification schemes, with different variables being selected - and different random datasets being generated for training. In particular, it is very likely that roughly 40% of your random trees will be trained without instances of class #2. And your toy dataset is not well suited for randomized methods - drop just one variable (say, last one), and you can not reliably distinguish between instances of classes #2 and #4.So, it is completely normal that on such small toy dataset you get such results. Try training on larger dataset, with noise being added to inputs.

 Author: antonysoldatov [ Thu Jan 04, 2018 5:28 am ] Post subject: Re: Problem with random forest Thank you for reply and your advise!

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