機器學習簡報 machine learning

Warm-up Basic Knowledge Preparation

Concept and Techniquesof Machine LearningWill Kuanin

COPYRIGHT2016 eBizprise Inc. & eBizprise Technology (TJ) Ltd.C2B()IT 2016.32016.4BC Foundation

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COPYRIGHT2016 eBizprise Inc. & eBizprise Technology (TJ) Ltd.qualitative attribute

quantitative attribute

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COPYRIGHT2016 eBizprise Inc. & eBizprise Technology (TJ) Ltd.Concept of Machine Learning Algorithms



Coursera


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Weak AI ( Artificial Narrow Intelligence )

?

+ ?

COPYRIGHT2016 eBizprise Inc. & eBizprise Technology (TJ) Ltd. vs. (Supervised Learning)

IF-THEN(Production Rule)

(Decision Tree)(SVM)(Random Forest)(KNN)(Unsupervised Learning)

(Cluster Analysis)(EM)

COPYRIGHT2016 eBizprise Inc. & eBizprise Technology (TJ) Ltd.(positive example)(negative example)Semi-supervised Learning

/


Reinforcement Learning(active learning)

COPYRIGHT2016 eBizprise Inc. & eBizprise Technology (TJ) Ltd.Clustering Analysis(similarity)(dissimilarity)(clusters)



R




COPYRIGHT2016 eBizprise Inc. & eBizprise Technology (TJ) Ltd.K-Means

Fuzzy C-Means

Dirichlet

Canopy

Spectral Clustering


COPYRIGHT2016 eBizprise Inc. & eBizprise Technology (TJ) Ltd.K(K-Means)


COPYRIGHT2016 eBizprise Inc. & eBizprise Technology (TJ) Ltd.1. KK(K)

2.

3. ()

4.

5. 34

COPYRIGHT2016 eBizprise Inc. & eBizprise Technology (TJ) Ltd.(K = 3)





COPYRIGHT2016 eBizprise Inc. & eBizprise Technology (TJ) Ltd.K-Means Pros and Cons of K-Means Advantages

COPYRIGHT2016 eBizprise Inc. & eBizprise Technology (TJ) Ltd.Disadvantages

K(K- Medoids)

(Soft Clustering)

K(K-Mode)


Fuzzy C-Means

Dirichlet

Canopy

Spectral Clustering


COPYRIGHT2016 eBizprise Inc. & eBizprise Technology (TJ) Ltd.C-Means(Fuzzy C-Means Clustering, FCM)Soft K-MeansFCMK-Meansx0-1x



Riris150

51.Sepal Length()2.Sepal Width ()3.Petal Length()4.Petal Width ()5.Class()

SetosaVersicolorVirginica

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..



FCM35023

COPYRIGHT2016 eBizprise Inc. & eBizprise Technology (TJ) Ltd.Fuzzy c-means clustering with 3 clusters

Cluster centers: [,1] [,2] [,3]5.003653 3.412805 1.4847765.874036 2.760273 4.3825236.793625 3.054511 5.644350

Closest hard clustering: [1] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 [43] 1 1 1 1 1 1 1 1 3 2 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 2 2 2 2 2 2 [85] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 2 3 3 3 3 2 3 3 3 3 3 3 2 2 3 3 3 3 2 3 2 3 2 3 3[127] 2 2 3 3 3 3 3 3 3 3 3 3 2 3 3 3 2 3 3 3 2 3 3 2


Memberships..


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COPYRIGHT2016 eBizprise Inc. & eBizprise Technology (TJ) Ltd.Things Owen Wilson Says

COPYRIGHT2016 eBizprise Inc. & eBizprise Technology (TJ) Ltd.as crazy as a road lizard

P( ) p( ) x p( ) p( | A) x p(A | ) p( | B) x p(B | )+


p | p( | )p( )

COPYRIGHT2016 eBizprise Inc. & eBizprise Technology (TJ) Ltd.Topic Model10%90%9



Fuzzy C-Means

Dirichlet

Canopy

Spectral Clustering


COPYRIGHT2016 eBizprise Inc. & eBizprise Technology (TJ) Ltd.Dirichlet DistributionPeter Gustav Lejeune DirichletDirichlet Process

(Natural Language Processing, NLP)Topic Model


COPYRIGHT2016 eBizprise Inc. & eBizprise Technology (TJ) Ltd.Latent Dirichlet Allocation, LDALDA(Latent Dirichlet allocation)kLDA

LDABlei, David M.Jordan, Michael I2003


COPYRIGHT2016 eBizprise Inc. & eBizprise Technology (TJ) Ltd.doc-topic Ktopictopic-word VKtopic-word

doc-topicdoc-topicztopicztopic-word

PLSA Model(Probabilistic Latent Semantic Analysis)



PLSA Model

KV

COPYRIGHT2016 eBizprise Inc. & eBizprise Technology (TJ) Ltd.doc-topictopic-word

K

doc-topicdoc-topicztopicKzLDA



Latent Dirichlet Allocation, LDAPLSA Model

LDA


Fuzzy C-Means

Dirichlet

Canopy

Spectral Clustering


COPYRIGHT2016 eBizprise Inc. & eBizprise Technology (TJ) Ltd.CanopyRecallK-Means - (e.g. )

K-Means


COPYRIGHT2016 eBizprise Inc. & eBizprise Technology (TJ) Ltd.(list) T1, T2T1 > T2

listCanopylist

listCanopyT1Canopy21

機器學習簡報 machine learning

Data & Analytics