Technical requirements

The code presented in this chapter requires:

• Python 3.5+ (Anaconda distribution: https://www.anaconda.com/distribution/ is highly recommended)
• Libraries:
  • SciPy 0.19+
  • NumPy 1.10+
  • scikit-learn 0.20+
  • pandas 0.22+
  • Matplotlib 2.0+
  • seaborn 0.9+

The dataset can be obtained through UCI. The CSV file can be downloaded from https://archive.ics.uci.edu/ml/machine-learning-databases/breast-cancer-wisconsin/wdbc.data and doesn't need any preprocessing except for the addition of the column names that will occur during the loading stage.

The examples are available on the GitHub repository:

https://github.com/PacktPublishing/HandsOn-Unsupervised-Learning-with-Python/Chapter02.