model_build

model_train.py

#Creating a list of Pipeline with well-known ML models
from sklearn.pipeline import make_pipeline
from sklearn.naive_bayes import MultinomialNB,ComplementNB
from sklearn.linear_model import LogisticRegression, RidgeClassifier
from sklearn.svm import SVC
from sklearn.ensemble import RandomForestClassifier
from sklearn.feature_extraction.text import CountVectorizer, TfidfVectorizer
from sklearn.tree import DecisionTreeClassifier

pipelines=[]
for model in [DecisionTreeClassifier(), MultinomialNB(), ComplementNB(), 
              LogisticRegression(solver='saga'), RidgeClassifier(solver='auto'), SVC(),RandomForestClassifier()]:
    pipeline=make_pipeline(TfidfVectorizer(), model)
    pipelines.append(pipeline)

#Training the model
import time
training_time=[]
for pipeline in pipelines:
    start=time.time()
    pipeline.fit(X_train, y_train)
    stop=time.time()
    training_time.append(stop-start)