In this blog we are going to hands on the Credit Card Fraud Detection Prediction using different models Like (KNN, Decesion Tree Classifier, AdaBoost Classifier , Naive Bayes. We will check which model is giving us high accuracy and which model will fit in with database.
import math
import pandas as pd
import datetime
import pandas_datareader as web
import numpy as np
import seaborn as sns
import statsmodels.api as sm
from sklearn.preprocessing import MinMaxScaler
from sklearn.tree import DecisionTreeRegressor
from sklearn.linear_model import LinearRegression
from sklearn.model_selection import train_test_split
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense, LSTM, Bidirectional, Dropout, Activation, GRU
from plotly.graph_objs import *
from plotly.offline import init_notebook_mode, iplot, iplot_mpl
import matplotlib
import matplotlib.pyplot as plt
matplotlib.style.use('seaborn')
In today’s age where we think twice to buy or consume any product or any service. We check the testimonies or reviews of that particular product service. In other words we check reviews given by previous customer wheater the product is worth spending money or not. From the reviews of that product or service we can get the sentiments of previous buyers.