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Banking code in java

on September 01, 2022

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LINEAR REGRESSION

LINEAR REGRESSION What is linear regression? Linear regression is a common method to model the relationship between a dependent variable and one or more independent variables. Linear models are developed using the parameters which are estimated from the data. SOURCE CODE: import numpy as np import matplotlib.pyplot as plt def estimate_coef(x, y): # number of observations/points n = np.size(x) # mean of x and y vector m_x = np.mean(x) m_y = np.mean(y) # calculating cross-deviation and deviation about x SS_xy = np.sum(y*x) - n*m_y*m_x SS_xx = np.sum(x*x) - n*m_x*m_x # calculating regression coefficients b_1 = SS_xy / SS_xx b_0 = m_y - b_1*m_x return (b_0, b_1) def plot_regression_line(x, y, b): # plotting the actual points as scatter plot plt.scatter(x, y, color = "m", marker = "o", s = 30) # predicted response vector y_pred = b[0] + b[1]*x # plotting the regression line plt.plot(x, y_pred, color = "g") # putting l...

MULTIPLE REGRESSION

What is multiple regression analysis? Multiple regression analysis is a statistical technique that analyzes the relationship between two or more variables and uses the information to estimate the value of the dependent variables. In multiple regression, the objective is to develop a model that describes a dependent variable y to more than one independent variable. S:OURCE CODE import pandas from sklearn import linear_model df = pandas.read_csv("data.csv") X = df[['Weight', 'Volume']] y = df['CO2'] regr = linear_model.LinearRegression() regr.fit(X, y) #predict the CO2 emission of a car where the weight is 2300kg, and the volume is 1300cm3: predictedCO2 = regr.predict([[2300, 1300]]) print(predictedCO2) OUTPUT [107.289544] [107.2087328] [107.2087328] [107.2087328]

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