[ 机器学习 - 吴恩达 ] | 1-3 Supervised Learning

Housing price prediction

• Supervised Learning: "right answers" given.
• Regression: Predict continuous (连续的) valued output (price)

Breast cancer (malignant (恶性的), benign (良性的))

• Classification: Dicrete (离散的) valued output (0 or 1)
• 肿瘤大小是判断癌症是否良性的重要特征，除此之外，还需要：
  • Age
  • Clump Thickness (肿瘤块的厚度)
  • Uniformity of Cell Size (细胞大小的均匀性)
  • Uniformity of Cell Shape (细胞形状的均匀性)
  • ...

You're running a company, and you want to develop learning algorithms to address each of two problems.
Problem 1: You have a large inventory (库存) of identical (相同的) items. You want to predict how many of these items will sell over the next 3 months.
Problem 2: You'd like software to examine individual (个人) customer accounts, and for each account decide if it has been hacked/compromised (黑/入侵).

Q-1: Should you treat these as classification or as regression problems?
Answer: C
? A: Treat both as classification problems.
? B: Treat problem 1 as a classification problem, problem 2 as a regression problem.
? C: Treat problem 1 as a regression problem, problem 2 as a classification problem.
? D: Treat both as regression problems.