Applied Supervised Learning with R

R provides excellent visualization features that are essential for exploring data before using it in automated learning.

Applied Supervised Learning with R helps you cover the complete process of employing R to develop applications using supervised machine learning algorithms for your business needs. The book starts by helping you develop your analytical thinking to create a problem statement using business inputs and domain research. You will then learn different evaluation metrics that compare various algorithms, and later progress to using these metrics to select the best algorithm for your problem. After finalizing the algorithm you want to use, you will study the hyperparameter optimization technique to fine-tune your set of optimal parameters. The book demonstrates how you can add different regularization terms to avoid overfitting your model.

By the end of this book, you will have gained the advanced skills you need for modeling a supervised machine learning algorithm that precisely fulfills your business needs.

R提供了出色的可視化功能，這對於在使用自動學習之前探索數據至關重要。

《Applied Supervised Learning with R》幫助您完整地使用R開發應用程序，並使用監督式機器學習算法滿足您的業務需求。本書首先幫助您培養分析思維，使用業務輸入和領域研究來創建問題陳述。然後，您將學習比較各種算法的不同評估指標，並進一步使用這些指標來選擇最適合您問題的算法。在確定要使用的算法後，您將學習超參數優化技術，以微調您的最佳參數集。本書演示了如何添加不同的正則化項以避免模型過度擬合。

通過閱讀本書，您將獲得進階技能，能夠精確地建模監督式機器學習算法，以滿足您的業務需求。