Using a data set

Inspiration

LHD Build 2021

What it does

Classifies email as spam

How we built it

python scikit-learn

STEPS

*STEP1 : * Install Scikit learn

pip install pandas scikit-learn

STEP2 : code

{import pandas as pd
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.naive_bayes import MultinomialNB, GaussianNB
from sklearn import svm
from sklearn.model_selection import GridSearchCV

dataframe = pd.read_csv("data_set.csv")
print(dataframe.head())

x = dataframe["EmailText"]
y = dataframe["Label"]

x_train, y_train = x[0:4457],y[0:4457]
x_test, y_test = x[4457:], y[4457:]

cv = CountVectorizer()
features = cv.fit_transform(x_train)

tuned_parameters = {'kernel':['linear','rbf'],'gamma':[1e-3,1e-4],'C':[1,10,100,1000]}

model = GridSearchCV(svm.SVC(),tuned_parameters)

model.fit(features,y_train)
print(model.best_params_)

features_test = cv.transform(x_test)
print(Accuracy of model :, model.score(features_test,y_test))
}

Built With

• python
• scikit-learn