function[]=eu(x0,y0,xn,h,f)
y(1)=y0;
j=(xn-x0)/h;
for i=1:j
y(i+1)=y(i)+h*f(x0,y(i))
x0=x0+h;
printf('\ny(%g)=%g\n',x0,y(i+1));
end
endfunction
Output:
deff('y=f(x,y)','y=2+sqrt(x*y)')
eu(1,1,1.6,0.1,f)
y(1.1)=1.3
y(1.2)=1.61958
y(1.3)=1.95899
y(1.4)=2.31858
y(1.5)=2.69874
y(1.6)=3.09994
1 Comments
@Slip – 1
ReplyDeleteQ. 1) Write a PHP script to keep track of number of times the web page has been accessed (Use Session
Tracking).
Ans:
Q. 2)Create ‘Position_Salaries’ Data set. Build a linear regression model by identifying independent and
Target variable. Split the variables into training and testing sets. Then divide the training and testing sets
Into a 7:3 ratio, respectively and print them. Build a simple linear regression model.
Ans:
Import numpy as np
Import pandas as pd
From sklearn.model_selection import train_test_split
From sklearn.linear_model import LinearRegression
# Create the Position_Salaries dataset
Data = {‘Position’: [‘CEO’, ‘charman’, ‘director’, ‘Senior Manager’, ‘Junior Manager’, ‘Intern’],
‘Level’: [1, 2, 3, 4, 5, 6],
‘Salary’: [50000, 80000, 110000, 150000, 200000, 250000]}
Df = pd.DataFrame(data)
# Identify the independent and target variables
X = df.iloc[:, 1:2].values
Y = df.iloc[:, 2].values
# Split the variables into training and testing sets with a 7:3 ratio
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, random_state=0)
# Print the training and testing sets
Print(“X_train:\n”, X_train)
Print(“y_train:\n”, y_train)
Print(“X_test:\n”, X_test)
Print(“y_test:\n”, y_test)
# Build a simple linear regression model
Regressor = LinearRegression()
Regressor.fit(X_train, y_train)
# Print the coefficients and intercept
Print(“Coefficients:”, regressor.coef_)
Print(“Intercept:”, regressor.intercept_)