logistic_regression

#Logistic Regression

##Description The Logistic Regression algorithm is a simple regression algorithm that can map an N-dimensional signal to a 1-dimensional signal.

The Logistic Regression algorithm is a supervised learning algorithm that can be used for regression for any type of N-dimensional signal. If you want to use Logistic Regression for classification, then you should use the specific classification version: Softmax.

The Logistic Regression algorithm is part of the GRT regression modules.

##Advantages The Logistic Regression algorithm is a simple regression algorithm that can map an N-dimensional signal to a 1-dimensional signal.

##Disadvantages Logistic Regression can only map an N-dimensional signal to a 1-dimension signal. If you need a regression algorithm that can map an N-dimensional to an M-dimensional signal, then you should try the MLP regression algorithm instead.

##Things To Know You should always enable scaling with Logistic Regression, as this will give you much better results.

##Training Data Format You should use the RegressionData data structure to train the Logistic Regression algorithm.

##Example Code Logistic Regression Example