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Chapter 1. Bayes Rule
Chapter 2. Classification
Chapter 3. Bayes & Classification
Chapter 4. Naive Bayes Classification
4. Kyunghoon Kim (UNIST) / 81Naive Bayes Classification using Python3 Aug 23, 2018 4
Probability
Probability : a way of quantifying the uncertainty associated with
events chosen from a some universe of events
확률 : 어떤 사건의 공간에서 특정 사건이 선택될 때 발생하는 불확실성을 측정하는 방법
"the probability of the event E"P(E)<latexit sha1_base64="keNIStIHW7F6nx85vrte+4f41yY=">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</latexit><latexit sha1_base64="gxcmSSCnJ8Gk9I9p2jGSaghzFN4=">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</latexit><latexit sha1_base64="gxcmSSCnJ8Gk9I9p2jGSaghzFN4=">AAACyXicjVHLSsNAFD2Nr1pfVZduQluhIpTEjS6LIghuKtgHtCLJdFpj0yQmE7EWV/6ACzf6Y9I/0L/wzjQFtYhOSHLm3HvOzL3XDlwnEoYxSmkzs3PzC+nFzNLyyupadn2jFvlxyHiV+a4fNmwr4q7j8apwhMsbQcitvu3yut07kvH6LQ8jx/fOxSDgF32r6zkdh1mCqFqhUjzeKVxm80bJUEufBmYC8uVca/d5VB5U/OwbWmjDB0OMPjg8CMIuLET0NGHCQEDcBYbEhYQcFed4QIa0MWVxyrCI7dG3S7tmwnq0l56RUjM6xaU3JKWObdL4lBcSlqfpKh4rZ8n+5j1UnvJuA/rbiVefWIErYv/STTL/q5O1CHRwoGpwqKZAMbI6lrjEqivy5vqXqgQ5BMRJ3KZ4SJgp5aTPutJEqnbZW0vF31WmZOWeJbkxPuQtacDmz3FOg9peyTRK5hlN+hDjlcYWcijSPPdRxgkqqJL3NZ7wglftVLvR7rT7caqWSjSb+La0x0+XJ5Nw</latexit><latexit sha1_base64="BIZOmwFmF1AwuFt9CVCnk3w13l8=">AAACyXicjVHLSsNAFD2Nr1pfVZdugq1QNyVxo8uiCIKbCvYBtUiSTuvYvEwmYi2u/AG3+mPiH+hfeGccQS2iE5KcOfeeM3PvdWOfp8KyXnLG1PTM7Fx+vrCwuLS8Ulxda6ZRlnis4UV+lLRdJ2U+D1lDcOGzdpwwJ3B91nKHBzLeumZJyqPwVIxi1g2cQcj73HMEUc1yvXK4XT4vlqyqpZY5CWwNStCrHhWfcYYeInjIEIAhhCDsw0FKTwc2LMTEdTEmLiHEVZzhDgXSZpTFKMMhdkjfAe06mg1pLz1TpfboFJ/ehJQmtkgTUV5CWJ5mqnimnCX7m/dYecq7jejvaq+AWIELYv/SfWb+VydrEehjT9XAqaZYMbI6T7tkqivy5uaXqgQ5xMRJ3KN4QthTys8+m0qTqtplbx0Vf1WZkpV7T+dmeJO3pAHbP8c5CZo7Vduq2idWqbavR53HBjZRoXnuooYj1NEg70s84BFPxrFxZdwYtx+pRk5r1vFtGffv2i2QYQ==</latexit>
사건(명제나 예측)이 일어날 확신에 대한 0과 1 사이의 숫자.
1: 명제가 확실히 참이거나 예측이 실제로 일어났음.
0: 명제가 확실히 거짓이거나 예측이 실제로 안 일어남.
5. Kyunghoon Kim (UNIST) / 81Naive Bayes Classification using Python3 Aug 23, 2018 5
Conditional Probability
조건부 확률 : B라는 조건이 주어졌을 때(given that),
A가 발생할 확률
P(A | B)<latexit sha1_base64="QvJ1tV7eLkO4mwmiKVGlbdFRfMs=">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</latexit><latexit sha1_base64="KOedgVcmuhreq4+zeIGokjOxt28=">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</latexit><latexit sha1_base64="KOedgVcmuhreq4+zeIGokjOxt28=">AAACznicjVHLTsJAFD3UF+ILdemmgZhgTEjrRpeIG5eYyCMBYtoy4IS+0k5JCCFu/QDd6mcZ/kD/wjtDSVRidJq2Z849587ce+3Q5bEwjFlGW1ldW9/Ibua2tnd29/L7B404SCKH1Z3ADaKWbcXM5T6rCy5c1gojZnm2y5r28ErGmyMWxTzwb8U4ZF3PGvi8zx1LENWulS71jsd7evXkLl80yoZa+jIwU1CsFDqnT7PKuBbk39BBDwEcJPDA4EMQdmEhpqcNEwZC4rqYEBcR4irOMEWOvAmpGCksYof0HdCunbI+7WXOWLkdOsWlNyKnjmPyBKSLCMvTdBVPVGbJ/pZ7onLKu43pb6e5PGIF7on9y7dQ/tcnaxHo40LVwKmmUDGyOifNkqiuyJvrX6oSlCEkTuIexSPCjnIu+qwrT6xql721VPxdKSUr906qTfAhb0kDNn+Ocxk0zsqmUTZvaNJVzFcWRyigRPM8RwXXqKGuOv6MF7xqNW2kTbWHuVTLpJ5DfFva4yek5JVu</latexit><latexit sha1_base64="AN2oWc+DrL+DjjEMmR+lbEO2qzc=">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</latexit>
Independent events Dependent events
사건 A와 B가 동시에 발생할 확률
P(A, B) = P(A)P(B)<latexit sha1_base64="rNWKNQhv2lMJZtRRTeXyqLzS9Uk=">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</latexit><latexit sha1_base64="+/EHptRWcmggVywN2FmaofaNqbs=">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</latexit><latexit sha1_base64="+/EHptRWcmggVywN2FmaofaNqbs=">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</latexit><latexit sha1_base64="JUmwVHCUwqPDZsVrsQEdRnB8ys0=">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</latexit>
P(A, B)<latexit sha1_base64="HUdgHDi91xUDiyMLOP3lz6ImTmQ=">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</latexit><latexit sha1_base64="ClEoqpJSKRqGYr9B/7GF+rld3MQ=">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</latexit><latexit sha1_base64="ClEoqpJSKRqGYr9B/7GF+rld3MQ=">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</latexit><latexit sha1_base64="WRD/snsD89v0yuj5jmQSfvyC4NE=">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</latexit>
P(A, B) = P(A | B)P(B)<latexit sha1_base64="cl3o6XTAe++qSNDgWXzRPYPl+h0=">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</latexit><latexit sha1_base64="rPg+gelnxoQpWILHFaJf6yO/05s=">AAAC4HicjVHLSsNAFD3GV62vqstuhhahopTEjW6Etm5cRrC2YEWSdNTBvEgmQiku3LkTwZU/4Fa/RvwD/QvvjBF8IDohybnn3nNm7lw39kUqTfN5xBgdG5+YLEwVp2dm5+ZLC4v7aZQlHm97kR8lXddJuS9C3pZC+rwbJ9wJXJ933LNtle+c8yQVUbgnBzE/DJyTUBwLz5FEHZXKdq3J1lhrhW0xu8aarBeIPoV2rbVyVKqadVMv9hNYOag2Kr3V2+fGwI5KT+ihjwgeMgTgCCEJ+3CQ0nMACyZi4g4xJC4hJHSe4wJF0mZUxanCIfaMvicUHeRsSLHyTLXao118ehNSMiyTJqK6hLDajel8pp0V+5v3UHuqsw3o7+ZeAbESp8T+pfuo/K9O9SJxjE3dg6CeYs2o7rzcJdO3ok7OPnUlySEmTuE+5RPCnlZ+3DPTmlT3ru7W0fkXXalYFXt5bYZXdUoasPV9nD/B/nrdMuvWLk26hfdVQBkV1GieG2hgBzba5H2Jezzg0XCNK+PauHkvNUZyzRK+LOPuDRjwmU8=</latexit><latexit sha1_base64="rPg+gelnxoQpWILHFaJf6yO/05s=">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</latexit><latexit sha1_base64="foDhYvSTQb2HYGngvLmgbnIcuM0=">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</latexit>
P(A | B) =
P(A, B)
P(B)<latexit sha1_base64="NPO/VJZirwRWAtx4jGtXIjXyChk=">AAAC6HicjVHLThRBFD20Ik91lKWbioRkTMykmw1uSEA3hLgYEgYmYYh219RgQb9SXW1CJnyAO3fErT/gVjf+BuEP9C84VTQJQohUp6vPPfee03XrJmWqKxuG5xPBg4eTj6amZ2bn5h8/edp69nynKmojVU8WaWH6SVypVOeqZ7VNVb80Ks6SVO0mR+9cfvezMpUu8m17XKr9LD7I9UjL2JL60FrstsW6GGR6KN6+EqtiMDKxHHfb668ZnxBwZ1XYCf0St0HUgMW1zf7vjwC6ResMAwxRQKJGBoUcljhFjIrPHiKEKMntY0zOEGmfVzjBLLU1qxQrYrJH3A8Y7TVszth5Vl4t+ZeUr6FSYImagnWG2P1N+HztnR17l/fYe7qzHfObNF4ZWYtPZP+nu6q8r871YjHCG9+DZk+lZ1x3snGp/a24k4trXVk6lOQcHjJviKVXXt2z8JrK9+7uNvb5P77SsS6WTW2Nv+6UHHB0c5y3wc5yJwo70RYn/R6Xaxov8BJtznMFa9hAFz16f8EP/MSv4DD4GpwG3y5Lg4lGs4B/VvD9Ak1fnGI=</latexit><latexit sha1_base64="7fXITZqB2wkxPb++wwZkDQeiCBI=">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</latexit><latexit sha1_base64="7fXITZqB2wkxPb++wwZkDQeiCBI=">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</latexit><latexit sha1_base64="J71okO2mjMbWCXQykU2g7DqVhFM=">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</latexit>
6. Kyunghoon Kim (UNIST) / 81Naive Bayes Classification using Python3 Aug 23, 2018 6
Bayes Rule
P(A|B) =
P(A B)
P(B)
=
P(B|A)P(A)
P(B)<latexit sha1_base64="cYIMT1olaa5XEJPkpVJ9WLoym+c=">AAADA3icjVFBTxNBGH1dRKGgVjhymUhI2gvZetELpi0XjzWxhYQSMjtMccN2dzM7a0IKR/+JN2+EK4lnrpoY/wGe/Au+GbaJSgzMZmffvPe9t/PNRHkSFzYMf9SCuQfzDx8tLNaXlh8/edp4tjIsstIoPVBZkpndSBY6iVM9sLFN9G5utJxEid6JjredvvNBmyLO0nf2JNf7E3mUxuNYSUvqoPG63xRdIU5FT7TElhiNjVTTfrM7UjIXvdYZMef61kzonXZblGfCQWM93Az9ELdBuwLrnc6v6y8A+lnjO0Y4RAaFEhNopLDECSQKPntoI0RObh9TcoYo9rrGGer0lqzSrJBkjzkfcbVXsSnXLrPwbsW/JHwNnQIb9GSsM8Tub8LrpU927P+ypz7T7e2E36jKmpC1eE/2Lt+s8r4+14vFGK98DzF7yj3julNVSulPxe1c/NGVZUJOzuFD6oZYeefsnIX3FL53d7bS69e+0rFuraraEj/dLnnB7X+v8zYYvthsE7/lTfdwMxawhudo8j5fooM36GPA7E+4wld8Cz4Gn4Pz4OKmNKhVnlX8NYLL32sypps=</latexit><latexit sha1_base64="x1xHxAR5Cr4KZJZbxESPE5ClnAk=">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</latexit><latexit sha1_base64="x1xHxAR5Cr4KZJZbxESPE5ClnAk=">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</latexit><latexit sha1_base64="hMbjCS9S/9InDaPZ/iLCRdbx4xM=">AAADA3icjVHNTttAGBzc8hd+GsqRy6oRUnJBDhe4gEh66TGVGkAiCK2XDVg4trVeV0KBI2/SW29Vr32BXqlU9Q3at+js1pEKCMFaXs/OfDPebzfKk7iwYfhrKnjxcnpmdm6+trC4tPyqvvJ6v8hKo3RfZUlmDiNZ6CROdd/GNtGHudFyFCX6ILp46/SDj9oUcZZ+sJe5Ph7JszQexkpaUif13V5TdIS4El3REjtiMDRSjXvNzkDJXHRb18ScazsToXvVaVGeCCf1RrgR+iEegnYFGqhGL6v/xACnyKBQYgSNFJY4gUTB5whthMjJHWNMzhDFXte4Ro3eklWaFZLsBeczro4qNuXaZRberfiXhK+hU2Cdnox1htj9TXi99MmOfSx77DPd3i75jaqsEVmLc7JP+SaVz/W5XiyG2PY9xOwp94zrTlUppT8Vt3PxX1eWCTk5h0+pG2LlnZNzFt5T+N7d2Uqv//aVjnVrVdWW+ON2yQtu37/Oh2B/c6NN/D5s7HWrq57DGt6gyfvcwh7eoYc+sz/hO27xI7gJPgdfgq//SoOpyrOKOyP49heXl6OE</latexit>
7. Kyunghoon Kim (UNIST) / 81Naive Bayes Classification using Python3 Aug 23, 2018 7
Bayes Rule
P(A|B) =
P(A B)
P(B)
=
P(B|A)P(A)
P(B)<latexit sha1_base64="cYIMT1olaa5XEJPkpVJ9WLoym+c=">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</latexit><latexit sha1_base64="x1xHxAR5Cr4KZJZbxESPE5ClnAk=">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</latexit><latexit sha1_base64="x1xHxAR5Cr4KZJZbxESPE5ClnAk=">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</latexit><latexit sha1_base64="hMbjCS9S/9InDaPZ/iLCRdbx4xM=">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</latexit>
P(H|D) =
P(H D)
P(D)
=
P(D|H)P(H)
P(D)<latexit sha1_base64="TD5n+I8aLG/dBRWeIwV6TpVfDCQ=">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</latexit><latexit sha1_base64="aFBRaFzod43F3j8JZIJb/oTsLO4=">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</latexit><latexit sha1_base64="aFBRaFzod43F3j8JZIJb/oTsLO4=">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</latexit><latexit sha1_base64="X5O0mW2ln/f1NxoQJv966GUixwI=">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</latexit>
12. Kyunghoon Kim (UNIST) / 81Naive Bayes Classification using Python3 Aug 23, 2018 12
Classification
placing things where they belong
사물을 속한 곳에 갖다 놓기
13. Kyunghoon Kim (UNIST) / 81Naive Bayes Classification using Python3 Aug 23, 2018 13
Classification
placing things where they belong
사물을 속한 곳에 갖다 놓기
class
or
category
14. Kyunghoon Kim (UNIST) / 81Naive Bayes Classification using Python3 Aug 23, 2018 14
Classification
placing things where they belong
사물을 속한 곳에 갖다 놓기
class
or
category
classification
15. Kyunghoon Kim (UNIST) / 81Naive Bayes Classification using Python3 Aug 23, 2018 15
Classification
16. Kyunghoon Kim (UNIST) / 81Naive Bayes Classification using Python3 Aug 23, 2018 16
Classification
17. Kyunghoon Kim (UNIST) / 81Naive Bayes Classification using Python3 Aug 23, 2018 17
Classification
18. Kyunghoon Kim (UNIST) / 81Naive Bayes Classification using Python3 Aug 23, 2018 18
Classification
Red
Orange
Yellow
Green
Blue
19. Kyunghoon Kim (UNIST) / 81Naive Bayes Classification using Python3 Aug 23, 2018 19
Classification
Red
Orange
Yellow
Green
Blue
Round
Long
Gourd
Flat
...
20. Kyunghoon Kim (UNIST) / 81Naive Bayes Classification using Python3 Aug 23, 2018 20
Classifiers
Classifiers
분류기
Statistical
통계적
Structural
구조적
Regression
회귀
Naive Bayes
나이브 베이즈
Bayesian networks
베이지안 네트워크
Rule-based
규칙 기반
Distance-based
거리 기반
Neural Networks
신경망
Production rule
생성 규칙
Decision trees
결정 트리
kNN
(k-최근접 이웃)
Learning vector
quantization
학습 벡터 양자화
Multilayer
perceptron
다층 퍼셉트론
21. Kyunghoon Kim (UNIST) / 81Naive Bayes Classification using Python3 Aug 23, 2018 21
Lifecycle of a classifier