- The Data Science Workshop
- Anthony So Thomas V. Joseph Robert Thas John Andrew Worsley Dr. Samuel Asare
- 102字
- 2021-06-11 18:27:22
3. Binary Classification
Overview
In this chapter, we will be using a real-world dataset and a supervised learning technique called classification to generate business outcomes.
By the end of this chapter, you will be able to formulate a data science problem statement from a business perspective; build hypotheses from various business drivers influencing a use case and verify the hypotheses using exploratory data analysis; derive features based on intuitions that are derived from exploratory analysis through feature engineering; build binary classification models using a logistic regression function and analyze classification metrics and formulate action plans for the improvement of the model.
推薦閱讀
- 在最好的年紀學Python:小學生趣味編程
- C程序設計簡明教程(第二版)
- 測試驅動開發:入門、實戰與進階
- Mastering SVG
- Cross-platform Desktop Application Development:Electron,Node,NW.js,and React
- Learning C++ Functional Programming
- Python Deep Learning
- Groovy for Domain:specific Languages(Second Edition)
- Learning SciPy for Numerical and Scientific Computing(Second Edition)
- Android玩家必備
- 從零開始學C#
- JavaScript機器人編程指南
- Managing Microsoft Hybrid Clouds
- SQL Server 入門很輕松(微課超值版)
- Getting Started with Python