percentagePrediction_LR

This code is an implementation of a linear regression model to predict the percentage score based on the number of hours studied. It uses the pandas library to read and manipulate data from a CSV file, matplotlib library to visualize the data, and scikit-learn library to perform machine learning tasks.

The first part of the code loads the data from a CSV file using the read_csv method from pandas and then plots the data using matplotlib. The x-axis represents the hours studied, and the y-axis represents the percentage score.

import pandas as pd import numpy as np import matplotlib.pyplot as plt from sklearn.linear_model import LinearRegression

Load the data

url = "http://bit.ly/w-data" data = pd.read_csv(url)

Plot the data

data.plot(x='Hours', y='Scores', style='o') plt.title('Hours vs Percentage') plt.xlabel('Hours studied') plt.ylabel('Percentage Score') plt.show()

The second part of the code prepares the data by splitting it into training and testing sets using train_test_split from scikit-learn. It also creates X and y arrays containing the input and output variables, respectively.

Prepare the data

X = data.iloc[:, :-1].values y = data.iloc[:, 1].values

Split the data into training and testing sets

from sklearn.model_selection import train_test_split X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=0)

The third part of the code trains the linear regression model using the fit method from scikit-learn. It then predicts the test set results using the predict method.

Train the model

regressor = LinearRegression() regressor.fit(X_train, y_train)

The final part of the code predicts the percentage score for a given number of hours studied (9.25 hours) using the trained model and the predict method. The result is displayed on the console using the print function.

Predict the test set results

y_pred = regressor.predict(X_test)

Predict the percentage score for 9.25 hours of study per day

hours = 9.25 score = regressor.predict([[hours]]) print("Predicted score for {} hours of study per day: {:.2f}%".format(hours, score[0])) CODE IMPLEMENTATIONM - https://youtu.be/s5msenMCftQ