Project 2 - EDA on Vehicle Insurance Customer Data

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Thank you..... Note: There is no such column rating in dataset. Based on this Quality is taken as rating Parameter. There is no such type Sweet Wine, Residual Suagar Ingredient give Sweetness of Wine. So This Taken as Sweetness Parameter

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In this project I was learn to check accuracy of given dataset using different algorithms like Logistic Regression,KNN,SVM,DT,RF algorithms. import timeStart_time = time.time()import pandas as pdimport numpy as npfrom sklearn.model_selection import train_test_splitfrom sklearn.preprocessing import StandardScalerfrom sklearn.linear_model…

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1.Pros and cons of SVM Ans. Advantages: SVM works relatively well when there is a clear margin of separation between classes. SVM is more effective in high dimensional spaces. SVM is effective in cases where the number of dimensions is greater than the number of samples. SVM is relatively memory efficient Disadvantages:…

2.Difference between L1 & L2 Gradient descent method T Here L1 is the mean absolute error L2 is the mean squared error. The mean absolute error is an average of the all absolute errors. The mean absolute error is a common measure of estimate error in time series analysis. The mean squared error of an estimator measures…

1.Calculate all 4 business moments using pen and paper for the below data set? Mean `mu` =∑ X x P(X) = (0x0.35) +(1 x0.25) +(2 x0.15) +(3x0.15) +(4x0.10) =1.4 Variance `sigma^2`=`sum(X_i-mu_x)^2 X P(x)` =(0-0)2 X(0.35) +(1-0.25)2 X(0.25) +(2-0.3)2 X(0.15) +(3-0.45)2 X(0.15) +(4-0.4)2X(0.1) =0+0.140+0.4335+0.9753+1.296…

1.Why there is a difference in the formula of variance for population and sample The Formula for Variance of Sample is `s^2 = (sum_(i=1)^n (x_i-mu)^2)/(n-1)` The Formula for Population Variance is `sigma^2 = (sum_(i=1)^n (x_i-mu)^2)/N` This used for the Concepts of degrees of Freedom. For the population Variance we find…

In this project I was learn PCA, K-means Clustering, and Hierchical usage detail. and Same output given by all algorithms also.

In this project i explore my self alot. i enjoyed alot. and i was use views, cursor,union keyword arithmetic opetors and not null keyword etc.,   2.Import all .csv files into MySQL i import like this remaining files. these are the tables.   5.Import first 1500 rows of tables (College_A_HS, College_A_SE, College_A_SJ, College_B_HS,…

due to this project i was get clarity about total concepts upto week 6. im glad about this but i loss my patience due to this and i had wait upto 20 hours to importing given data. but it was imported only 20000 rows. iam worried about it.so i was prepare code for 20000 rows it will applied to all data present in users_data.…

Project 2: import numpy as np import pandas as pd import os from numpy import * from pandas import * import warnings warnings.filterwarnings('ignore') import string reading the files using pandas DataFrame1 = pd.read_csv(r"C:Userssambasambacustomer details.csv") DataFrame2 = pd.read_csv(r"C:Userssambasambacustomer_policy…

1A. #1. Database-Software Interface import pickle #serialization package import os def SavingDictionary(tmp_dict): try: # 'wb' means open file with writing binary mode with open('words.txt', 'wb') as dictionary: pickle.dump(tmp_dict, dictionary) # dictionary = open('words.txt', 'wb') # pickle.dump(tmp_dict, dictionary)…