Day1.資料探勘研究與實務_9/14_Week01上課筆記_Data Mining: Introduction

What is Data Mining?

Input Data -> Data Preprocessing -> Data mining -> Postprocessing -> Information

Data Preprocessing

Feature Selection

Normalization

Dimensionality Reduction

Data Subsetting

Postprocessing

Filtering Patterns

Visualization

Pattern Interpretation

Data Mining Tasks 

1.Clustering

Finding groups of objects such that the objects in a group will be similar (or related) to one another and different from (or unrelated to) the objects in other groups.

2.Predictive Modeling(Classification , Regression )

Classification

Find a model  for class attribute as a function of the values of other attributes

例如:

Fraud Detection(欺詐識別) , Churn prediction for telephone customers(電話客戶流失預測)

Regression

Predict a value of a given continuous valued variable based on the values of other variables, assuming a linear or nonlinear model of dependency.

3.Association Rules

4.Anomaly Detection