NAIVE BAYES MODULE

 

Ex N0                                    Implement Naive Bayes models

CLICK HERE >> PROGRAM

Aim

To write a python program to implementation of naive bayes model using a titanic dataset.

Algorithm

1. Import the required libraries: numpy, pandas, sklearn, and warnings.

2. Suppress the warnings.

3. Mount Google Drive to access the Titanic dataset in CSV format.

4. Read the dataset from the CSV file and print the shape of the dataframe.

5.Convert the 'Sex' column values to numerical values and print the head of the dataframe.

6. Select the required columns for input features and output variable.

7. Split the data into training and testing sets.

8. Create a Gaussian Naive Bayes model.

9. Fit the model to the training data.

10. Take input from the user for a person's Pclass number, gender, age, and fare.

11. Create a list containing the input values.

12. Predict the output for the given input using the fitted model.

13. Print the prediction as whether the person might survive or not.

14. Predict the output for the test set.

15. Calculate and print the accuracy score.

Result

Thus the implementation of Naive Bayes model has been executed successfully.