๋ถ๋ฅ ์ ์ฒด๋ณด๊ธฐ (285) ์ธ๋ค์ผํ ๋ฆฌ์คํธํ Information Theory preparing for WS 2019/20 Advanced Statistical Learning _ Final exam https://docs.google.com/document/d/1wDxMuZuq82QiEyrRgqiRozLhOzVj6ds-b4z9Tcvajvk/edit?usp=sharing Information Theory ์ผ๋ถ Word ๊ธฐ๋ฅ์ Google ๋ฌธ์์ ํ์ํ ์ ์์ผ๋ฉฐ ๋ณ๊ฒฝ์ฌํญ์ด ์ ์ฅ๋์ง ์์ต๋๋ค. ์ธ๋ถ์ ๋ณด ๋ณด๊ธฐ docs.google.com ์ฐธ๊ณ ํ ์ฌ์ดํธ๋ค โกฬ - TU Dortmund ASL moodle https://www.lsf.tu-dortmund.de/qisserver/rds?state=user&type=0 Technische Universität Dortmund HERZLICH.. B-Splines preparing for WS 2019/20 Advanced Statistical Learning _ Final exam https://docs.google.com/document/d/1NdQX-WtXY78KwO13jLUH7ujaCppqSWSJOftRTC1sWxg/edit?usp=sharing B-Splines ์ผ๋ถ Word ๊ธฐ๋ฅ์ Google ๋ฌธ์์ ํ์ํ ์ ์์ผ๋ฉฐ ๋ณ๊ฒฝ์ฌํญ์ด ์ ์ฅ๋์ง ์์ต๋๋ค. ์ธ๋ถ์ ๋ณด ๋ณด๊ธฐ docs.google.com ์ฐธ๊ณ ํ ์ฌ์ดํธ๋ค โกฬ - TU Dortmund ASL moodle https://www.lsf.tu-dortmund.de/qisserver/rds?state=user&type=0 2020 01_ๆฅๅธธ Univariate and Linear Modeling preparing for WS 2019/20 Advanced Statistical Learning _ Final exam https://docs.google.com/document/d/1itWxbfG1jFERiR3l74bjuG18wVYGBbkcDqVWV49rCpM/edit?usp=sharing Univariate and Linear Modelling ์ผ๋ถ Word ๊ธฐ๋ฅ์ Google ๋ฌธ์์ ํ์ํ ์ ์์ผ๋ฉฐ ๋ณ๊ฒฝ์ฌํญ์ด ์ ์ฅ๋์ง ์์ต๋๋ค. ์ธ๋ถ์ ๋ณด ๋ณด๊ธฐ docs.google.com ์ฐธ๊ณ ํ ์ฌ์ดํธ๋ค โกฬ - TU Dortmund ASL moodle https://www.lsf.tu-dortmund.de/qisserver/rds?state=user&type=0 Risk Minimization preparing for WS 2019/20 Advanced Statistical Learning _ Final exam https://docs.google.com/document/d/1D6ojkGmHpTAk8H1QEBE-unNA32QvIp_BIcc9jTKtxM8/edit?usp=sharing Risk Minimization ์ผ๋ถ Word ๊ธฐ๋ฅ์ Google ๋ฌธ์์ ํ์ํ ์ ์์ผ๋ฉฐ ๋ณ๊ฒฝ์ฌํญ์ด ์ ์ฅ๋์ง ์์ต๋๋ค. ์ธ๋ถ์ ๋ณด ๋ณด๊ธฐ docs.google.com ์ฐธ๊ณ ํ ์ฌ์ดํธ๋ค โกฬ - TU Dortmund ASL moodle https://www.lsf.tu-dortmund.de/qisserver/rds?state=user&type=0 Hypothesis Spaces and Capacity preparing for WS 2019/20 Advanced Statistical Learning _ Final exam https://docs.google.com/document/d/1YCPVN5X5QARzxE3y10vxG934ofAxtypJY_8A3BIc6Z8/edit?usp=sharing Hypothesis Spaces and Capacity ์ผ๋ถ Word ๊ธฐ๋ฅ์ Google ๋ฌธ์์ ํ์ํ ์ ์์ผ๋ฉฐ ๋ณ๊ฒฝ์ฌํญ์ด ์ ์ฅ๋์ง ์์ต๋๋ค. ์ธ๋ถ์ ๋ณด ๋ณด๊ธฐ docs.google.com ์ฐธ๊ณ ํ ์ฌ์ดํธ๋ค โกฬ - TU Dortmund ASL moodle https://www.lsf.tu-dortmund.de/qisserver/rds?state=user&type=0 Classification preparing for WS 2019/20 Advanced Statistical Learning _ Final exam https://docs.google.com/document/d/1-gs2dJtME6X-gayhWaLxHf9lvWIcqSgnbmZZzBo7AKo/edit?usp=sharing Classification Classification ๋ถ๋ฅ Classification Tasks ์ง๋ํ์ต ์๊ณ ๋ฆฌ์ฆ์ผ๋ก ๋ค์ํ X ๋ณ์๋ค๊ณผ ๋ฏธ๋ฆฌ ์ ์๋ class ๋ณ์ (=Y ๋ณ์)์์ ๊ด๊ณ๋ฅผ ๋ฐํ๋ ๊ณผ์ In classification, we aim at predicting a discrete output y y = {C1, …, Cg} with 2ggiven data D y = {0,1} or y = {-1, 1.. France, Paris ์ด์ 1 ยทยทยท 6 7 8 9 10 11 12 ยทยทยท 36 ๋ค์