Challenges Data Stream:(a)Infinite Length (b)Evolving Nature ◆Single Pass Handling ◆Memory Limitation ◆Low Time Complexity ◆Concept Drift
Challenges Data Stream: (a) Infinite Length (b) Evolving Nature Single Pass Handling Memory Limitation Low Time Complexity Concept Drift
What is concept drift? In predictive analytics and machine learning,the concept drift means that the statistical properties of the target variable, which the model is trying to predict,change over time in unforeseen ways. In a word,the probability distribution changes. ·Change in P(c) ·Change in P(X) ·Change in P(ClX)
What is concept drift？ In predictive analytics and machine learning, the concept drift means that the statistical properties of the target variable, which the model is trying to predict, change over time in unforeseen ways. In a word, the probability distribution changes. • Change in P(C) • Change in P(X) • Change in P(C|X)
Real concept drift vs.Virtual concept drift Original data Real concept drift Virtual drift ● p(yX)changes p(X)changes,but not p(ylX) P(C,IX)=P(C)P(XIC,) P(X)
Real concept drift vs. Virtual concept drift P(C ) P(X | C ) (C | X) P(X) i i P i
Example:Concept-Drift Current hyperplane 0 O 0 0 0 O 0 6 0 00 0 00 8 000 8 000 0 O Previous hyperplane A data chunk Negative instance● Instances victim of concept-drift Positive instance o
Example: Concept-Drift Negative instance Positive instance A data chunk Current hyperplane Previous hyperplane Instances victim of concept-drift
1,Concept Drift Detection
1、 Concept Drift Detection