Mindmap
IDA
Inhalt der Mindmap
IDA
PCA
- Expectation
- Variance
Mining Text Data
- doc Vectors
- Clustering/Classification
- Why?
- data sparse
- Synonmy&Polysemy
- How?
- LSA
- PCA
- Concept Space
- Semantic relationship
- co-occurence of terms
- Semantic relationship
- LSA
- Why?
Page Rank
- Energy
Clustering
- codebook vector
- initialization
- iterative method
- initialization
- How many
- Where
- codebook vector
Classification
- K-NN
- Majority Vote
- Two extremes
- K = N
- too simple
- K = 1
- too complex
- Best K
- precision in classifying my data
- stability across mutiple sample
- K = N
- K-fold
- K-NN
Informationen
- Beschreibung
- Mindmap am IDA, erstellt von Han Jiang am 27/05/2014.
- Erstellt von
- Han Jiang · Mai 2014
- Aktualisiert
- 19 Feb 2016
- Aufrufe
- 21
- Bewertung