Logistic Regression - Project



Logistic Regression Project

In this project I will be working with a fake advertising data set, indicating whether or not a particular internet user clicked on an Advertisement. I will try to create a model that will predict whether or not they will click on an ad based off the features of that user.
This data set contains the following features:

  • 'Daily Time Spent on Site': consumer time on site in minutes
  • 'Age': cutomer age in years
  • 'Area Income': Avg. Income of geographical area of consumer
  • 'Daily Internet Usage': Avg. minutes a day consumer is on the internet
  • 'Ad Topic Line': Headline of the advertisement
  • 'City': City of consumer
  • 'Male': Whether or not consumer was male
  • 'Country': Country of consumer
  • 'Timestamp': Time at which consumer clicked on Ad or closed window
  • 'Clicked on Ad': 0 or 1 indicated clicking on Ad


Import Libraries
     
First of all, import the libraries



Get the Data

Then get the data


Next, check information of data





Exploratory Data Analysis


I'll use seaborn to explore the data














Logistic Regression
now, it's time to do a train test split

Predictions and Evaluations

Conclusion

if we hold all other feature fixed the result of prediction would correct around ~90%

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