gaussianNB#
- swordfish.function.gaussianNB()#
Conduct the Naive Bayesian classification.
- Parameters:
Y (Constant) – A vector with the same length as table X. Each element of labels indicates the class that the correponding row in X belongs to.
X (Constant) – A table indicating the training set. Each row is a sample and each column is a feature.
varSmoothing (Constant, optional) – A positive floating number indicating the portion of the largest variance of all features that is added to variances for calculation stability. The default value is 1e-9.
- Returns:
A dictionary with the following keys:
model: a RESOURCE data type variable. It is an internal binary resource generated by function gaussianNB and to be used by function predict.
modelName: string “GaussianNB”.
varSmoothing: varSmoothing parameter value.
- Return type: