Importing Required Libraries
Before building any machine learning model, we need to import the required Python libraries. Each library provides tools for data manipulation, visualization, text processing, and machine learning.
Libraries Used
Pandas
Used for loading and manipulating datasets.
NumPy
Provides numerical operations.
Matplotlib
Creates visualizations and graphs.
Seaborn
Produces statistical visualizations.
Scikit-learn
Provides machine learning algorithms and evaluation metrics.
NLTK
Offers Natural Language Processing tools such as stopword removal and lemmatization.
Code
# Data manipulation
import pandas as pd
import numpy as np
# Data visualization
import matplotlib.pyplot as plt
import seaborn as sns
# Text preprocessing
import re
import nltk
from nltk.corpus import stopwords
from nltk.stem import WordNetLemmatizer
# Machine Learning
from sklearn.model_selection import train_test_split
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.linear_model import LogisticRegression
# Evaluation Metrics
from sklearn.metrics import (
accuracy_score,
classification_report,
confusion_matrix
)Download Required NLP Resources
nltk.download('stopwords')
nltk.download('wordnet')
nltk.download('omw-1.4')Fake Review Detection System using Machine Learning
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