Final presentationProject 4: Machine Learning

Josef Koini [ #24 ]Knowledge Discovery and Data Mining 2

TU Graz

29 June 2017

Recapitulation

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What happened before...#Problem: automatic tagging of songs#Data set: Last.fm data set#Planned approach: Classification with Naive Bayes

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Approach

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Example{

"artist": "Neil Diamond","timestamp": "2011-08-09 02:43:27.936416","similars": [["TRWERMW128F92D19EB", 0.891814],

...,["TREJCAS128F9309618", 0.00048260300000000001]],

"tags": [["Soundtrack", "100"],["soft rock", "33"],["Neil Diamond", "33"],["brooklyn connections", "16"],["new york connections", "16"],["stage-and-screen", "16"],...,["diamond", "16"], ["male vocalists", "16"],

["cinematic", "16"], ["american", "16"]],"track_id": "TRJFKKR128F92D1950","title": "Dear Father”

}

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Example{

"artist": "Neil Diamond","timestamp": "2011-08-09 02:43:27.936416","similars": [["TRWERMW128F92D19EB", 0.891814],

...,["TREJCAS128F9309618", 0.00048260300000000001]],

"tags": [["Soundtrack", "100"],["soft rock", "33"],["Neil Diamond", "33"],["brooklyn connections", "16"],["new york connections", "16"],["stage-and-screen", "16"],...,["diamond", "16"], ["male vocalists", "16"],

["cinematic", "16"], ["american", "16"]],"track_id": "TRJFKKR128F92D1950","title": "Dear Father”

}

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Feature preparation#Bag of words approach# Title# Artist

#Bigrams#Minimum feature appearance#Tf-idf#Feature selection#Removing tracks without tags from training set

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Classification#Scikit-learn#Multinomial Naive Bayes classifier#Top n tags#2 classifiers per tag# Title# Artist

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Results

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Evaluation#Accuracy#Precision#Recall#F1-measure

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Problems#Unbalanced classes#Tracks without tags

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Tags

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Tag distribution

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Accuracy

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86,12% 87,89%90,78%

87,66% 92,40% 94,51% 96,38% 97,71% 98,83% 99,31%

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Precision

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64,57% 64,38% 64,43%

42,54%

51,03% 49,47% 53,11% 55,51% 57,97% 59,05%

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Recall

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68,15% 63,28% 62,33%

65,30%

57,71% 54,63%

46,12% 40,15%

33,68% 29,29%

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F1

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66,31% 63,82% 63,36%

51,52% 54,17% 51,92% 49,37% 46,60% 42,60%

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Conclusion

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To put it in a nutshell...#Number of tags influences the strategy#Efficient method#Fairly good results

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Questions?Don‘t hesitate to ask ;)

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