Several concepts in Data Mining

Data Mining tasks

Predictive tasks:

---Classification (which is used for discrete target variables)

---Regression (which is used for continuous target variables)

Descriptive tasks:

---Association analysis (to discover patterns that describe strongly associated features in the data)

---Cluster analysis (to find groups of related observations)

---Anomaly detection (identify observations whose characteristics are significantly different from the rest of the data)

Types of Attributes

---Nominal

Examples: ID numbers, eye color, zip codes

---Ordinal

Examples: rankings (e.g., taste of potato chips on a scale from 1-10), grades, height in {tall, medium, short}

---Interval

Examples: calendar dates, temperatures in Celsius or Fahrenheit.

---Ratio

Examples: temperature in Kelvin, length, time, counts

bias是classifier产生的（比如分类器建立在一些假设条件基础上）
variance由数据集的选取产生
noise数据集的某个数据产生