Challenge - Classification of non-linear data

Challenge - Classification of non-linear data

In this lesson, you need to perform a classification task. Unlike the tasks we completed before, this dataset is non-linear. This means you can’t only use logistic regression. SVM is a good choice. (If you already learned the GBDR, it’s also a good choice.)

• Load the dataset from the file nonlinear.csv.
• Split the data into two parts, the test accounts for 20%. You can use 42 as the random seed
• Build an SVM model and fit it.
• Return the F1-score metric.

Note: You can load nonlinear.csv as this file is already on the platform. This dataset has three columns, col1, col2, and target. The target is the label.

If you are already familiar with pandas library, it’s easy for you to load this dataset. If not, you can click the Hint to get the code of loading data.