can we use GMDH for two or three class classiication
As I read in R package GMDH a function for short term forecasting of a univariate time series by using GMDH-type neural network algorithms. Can i use it for Iris Dataset?
At the moment there two GMDH packages in R: devtools::install_github("dratewka/rGMDH") library(rGMDH) m <- rGMDH::train(x,y) yh <- predict(m, x) and library(GMDH) out = fcast(data, input = 6, layer = 2, f.number = 1) Both are designed for short-term forecasting and you will not be able to use them for classification. However, by design, GMDH algorithms are very suitable for multi-variable classification. In fact, better than regression (see e.g. Section 5 in http://math.umaine.edu/~farlow/gmdh%20in%20pdf.pdf or Section 8 in The Review of Problems Solvable by Algorithms of the Group Method of Data Handling (GMDH) ). Unfortunately they have not been fully implemented in R yet. If interested, you may be able to implement it yourself using R base classes - E.g. See the first reference above to describe the exact algorithm.
Can someone give me an example how to count probabilities using Complementary Naive Bayes in Mahout?
Classification results interpretation (TFlearn, Keras)
discretization for feature selection in weka
ROC result interpretation
Classification using Mallet and MaxEntropy
Measuring Error Correlation of Classifiers
caffe: Confused about regression
How to cut a dendrogram in r
Building weka classifier
Does Orange data mining software has multi-layer perceptron classification?
User Classification in RapidMiner - output should be the user based on a fed test data
Error in building mean image file(Caffe)
caffe: probability distribution for regression / expanding classification (softmax layer) to allow 3D output
Does MLE produce a generative or discriminative classifier?
Basic Hidden Markov Model, Viterbi algorithm
Where do I write the code for LIBSVM?