task3

Data Reading

Read customer browsing behavior data from a CSV file.

The dataset contains visitor session information such as time spent on pages, number of pages viewed, and purchase outcome.

Preprocessing

Prepare the dataset for machine learning.

Handle missing values and convert categorical variables into numerical format so that the decision tree model can process the data correctly.

Train a Model

Split the dataset into training and testing sets.

Use the training data to build a Decision Tree model that learns patterns in customer browsing behavior and predicts whether a visitor will make a purchase.

Score the Model

Apply the trained model to the test data.

Evaluate the prediction results using the Scorer node and measure model performance with accuracy and confusion matrix.