Efficient E-Mail Spam Detection Strategy Using Genetic Decision Tree Processing with NLP Features

Algorithm 1

Genetic Algorithm.

	Initialization:
Assign, No. of Documents = N;
Datapoints = X;
Target Inputs = Y;
StopwordRemoval = ;
Vectorizer = ;
TF-IDF =  ;
Assign, Dict = ;
Dict = Preprocessed data;
Initialization of ML Parameters;
Declaring ML Algorithm;
Def GA:
Initialization of GA parameters:
GenerationSize = G;
PopulationSize = P;
OffSpringSize = ;
MutationRate = M;
CrossoverRate = C;
StratifiedKF = K;
Assign, GA Module = G, P, , M, C;
Calculate: Survivor of Swarm;
for G in Generation do
for P in Population do
for i < K do
Calculate the Fitness = Survival;
Select two Individuals;
= Produce OffSpring;
OffSpring, M = Mutate;
return KScore
Calculate: Parameters;
return Parameters
Calculate: Measures;
Parameters, Data, Data = Measures;
return Accuracy
for t in test_size do
test size = x_test and y_test;
train size = x_train and y_train;
Call GA (train and test data);