vardhanshah / bayes-classifier Goto Github PK

Here, it is implementation of naive bayes algorithm with assumption of gaussian distribution
in python3.

Above implementation will take dataset as input and will train itself, As for the
prediction part, You can give another input file, otherwise it will use input dataset to predict
result and comparing it with original result.

both files should contain features, followed by original outcome.

file should contain data set as :
        
        feature 1,feature 2,[feature 3,...,],outcome
 
 in this manner.
(comma(,) is used to separate elements)

features can only be real numbers
and file name should contain atleast 1 character.


As the execution part, matplotlib module will be needed,if it is not available, you can use another source code
file, both source code file has same structure, but one file uses matplotlib to plot graph and another one don't
use it.
Execution input instruction:
Give
Needed: (1)-Input File Path/Name
Optional: (2)-No. of features needed for prediction
Optional: (3)-Give file for prediction task otherwise it will use the input file
for measure its accuracy

Note: input should be separated by space( )


Input in manner : (1) [(2) (3)] or (1) [(3) (2)] 

[] indicates optional.

for example:

    execute any .py file and give input 

    iris.data