Running a targetted marketing ads on facebook. The company wants to anaylze customer behaviour by predicting which customer clicks on the advertisement. Customer data is as follows:
Inputs:
- Name
- Country
- Time on Facebook
- Estimated Salary (derived from other parameters)
- Split the data in Train and Test
- Train and Test the model in the data set
- Visualize
- Predict Click on the ad
Open Google Colab https://colab.research.google.com/
- File
- Upload Notebook
- Run the Cells
Import the data set and visualize the data
- With Scatter plot
- With Box plot
- With Histogram
Transforming the data and Executing a training Test
With Confusion Matrix, checking on the accuracy
ploting the boundary using the trained classifier
- Run the classifier to predict the outcome on all pixels with resolution of 0.01
- Colouring the pixels with 0 or 1
- If classified as 0 it will be magenta, and if it is classified as 1 it will be shown in blue
Ploting all the actual training points
Visualising the Training set results for Tran and Test