\uc5ed \uc6e8\uc774\ube14\ub9bf \ubcc0\ud658<\/strong>: \ud544\ud130\ub9c1\ub41c \uc2e0\ud638\ub97c \ubcf5\uc6d0\ud558\uc5ec \ucd5c\uc885 \ub370\uc774\ud130\ub97c \ucd9c\ub825\ud569\ub2c8\ub2e4.<\/li>\n<\/ol>\n5.1 \uc0d8\ud50c \ucf54\ub4dc<\/h3>\n
\uc544\ub798\ub294 Python\uc5d0\uc11c PyWavelets \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \uc0ac\uc6a9\ud558\uc5ec \uc6e8\uc774\ube14\ub9bf \ubcc0\ud658\uc744 \uc801\uc6a9\ud558\ub294 \uc608\uc81c\uc785\ub2c8\ub2e4:<\/p>\n
import pywt\nimport numpy as np\n\n# \uc6d0\uc2dc \ub370\uc774\ud130 \uc0dd\uc131 (\uc608: \uc8fc\uac00 \ub370\uc774\ud130)\ndata = np.random.rand(512) \n\n# \uc6e8\uc774\ube14\ub9bf \ubcc0\ud658 \uc218\ud589 (Daubechies Wavelet \uc0ac\uc6a9)\ncoeffs = pywt.wavedec(data, 'db1')\nthreshold = 0.1\n\n# \uc7a1\uc74c \uc81c\uac70\ncoeffs_filtered = [pywt.threshold(c, threshold) for c in coeffs]\n\n# \uc5ed \uc6e8\uc774\ube14\ub9bf \ubcc0\ud658\ndata_filtered = pywt.waverec(coeffs_filtered, 'db1')\n <\/code><\/pre>\n6. \ubaa8\ub378 \ud559\uc2b5 \ubc0f \ud3c9\uac00<\/h2>\n
\uc6e8\uc774\ube14\ub9bf \ubcc0\ud658\uc744 \ud1b5\ud574 \uc7a1\uc74c\uc774 \uc81c\uac70\ub41c \ub370\uc774\ud130\ub97c \ubc14\ud0d5\uc73c\ub85c \uba38\uc2e0\ub7ec\ub2dd \ubc0f \ub525\ub7ec\ub2dd \ubaa8\ub378\uc744 \uad6c\ucd95\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc77c\ubc18\uc801\uc778 \ubaa8\ub378 \ud559\uc2b5 \uacfc\uc815\uc740 \ub2e4\uc74c\uacfc \uac19\uc2b5\ub2c8\ub2e4:<\/p>\n
\n- \ub370\uc774\ud130 \ubd84\ud560<\/strong>: \ud559\uc2b5 \ub370\uc774\ud130\uc640 \ud14c\uc2a4\ud2b8 \ub370\uc774\ud130\ub85c \ub098\ub204\uc5b4 \uacfc\uc801\ud569\uc744 \ubc29\uc9c0\ud569\ub2c8\ub2e4.<\/li>\n
- \ubaa8\ub378 \uc120\ud0dd<\/strong>: Random Forest, XGBoost, LSTM\uacfc \uac19\uc740 \ub2e4\uc591\ud55c \ubaa8\ub378\uc744 \uc2e4\ud5d8\ud569\ub2c8\ub2e4.<\/li>\n
- \ubaa8\ub378 \ud559\uc2b5<\/strong>: \ud559\uc2b5 \ub370\uc774\ud130\ub97c \uc0ac\uc6a9\ud558\uc5ec \ubaa8\ub378\uc744 \ud6c8\ub828\ud569\ub2c8\ub2e4.<\/li>\n
- \ubaa8\ub378 \ud3c9\uac00<\/strong>: \ud14c\uc2a4\ud2b8 \ub370\uc774\ud130\ub97c \uc0ac\uc6a9\ud558\uc5ec \ubaa8\ub378\uc758 \uc131\ub2a5\uc744 \ud3c9\uac00\ud569\ub2c8\ub2e4.<\/li>\n<\/ol>\n
6.1 \ubaa8\ub378 \ud3c9\uac00 \uc9c0\ud45c<\/h3>\n
\ubaa8\ub378\uc758 \uc131\ub2a5\uc744 \ud3c9\uac00\ud558\uae30 \uc704\ud55c \uc77c\ubc18\uc801\uc778 \uc9c0\ud45c\ub294 \ub2e4\uc74c\uacfc \uac19\uc2b5\ub2c8\ub2e4:<\/p>\n
\n- \uc815\ud655\ub3c4(Accuracy)<\/strong>: \uc804\uccb4 \uc0d8\ud50c \uc911 \uc62c\ubc14\ub974\uac8c \uc608\uce21\ud55c \ube44\uc728\uc785\ub2c8\ub2e4.<\/li>\n
- \uc815\ubc00\ub3c4(Precision)<\/strong>: \uc608\uce21\ud55c \uae0d\uc815 \uc0d8\ud50c \uc911 \uc2e4\uc81c \uae0d\uc815 \uc0d8\ud50c\uc758 \ube44\uc728\uc785\ub2c8\ub2e4.<\/li>\n
- \uc7ac\ud604\uc728(Recall)<\/strong>: \uc2e4\uc81c \uae0d\uc815 \uc0d8\ud50c \uc911 \uc62c\ubc14\ub974\uac8c \uc608\uce21\ud55c \ube44\uc728\uc785\ub2c8\ub2e4.<\/li>\n<\/ul>\n
7. \uacb0\ub860<\/h2>\n
\uba38\uc2e0\ub7ec\ub2dd \ubc0f \ub525\ub7ec\ub2dd\uc744 \ud65c\uc6a9\ud55c \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529\uc740 \uac15\ub825\ud55c \ub3c4\uad6c\uc77c \uc218 \uc788\uc9c0\ub9cc, \uc7a1\uc74c \ub370\uc774\ud130\uc758 \uc804\ucc98\ub9ac\ub97c \uc18c\ud640\ud788 \ud558\uba74 \uc131\ub2a5\uc774 \ud06c\uac8c \uc800\ud558\ub420 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc6e8\uc774\ube14\ub9bf \ubcc0\ud658\uc740 \uc7a1\uc74c \uc81c\uac70\uc758 \ud6a8\uacfc\uc801\uc778 \ubc29\ubc95\uc73c\ub85c, \ub2e4\uc591\ud55c \uc8fc\ud30c\uc218 \ub300\uc5ed\uc5d0\uc11c \uc2e0\ud638\ub97c \ubd84\uc11d\ud560 \uc218 \uc788\ub294 \uc7a5\uc810\uc744 \uc81c\uacf5\ud569\ub2c8\ub2e4. \ub530\ub77c\uc11c, \uc62c\ubc14\ub978 \uc804\ucc98\ub9ac \ub2e8\uacc4\ub97c \ud1b5\ud574 \ub354 \uc2e0\ub8b0\ud560 \uc218 \uc788\ub294 \ud2b8\ub808\uc774\ub529 \uc804\ub7b5\uc744 \uac1c\ubc1c\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n
8. \ucc38\uace0 \ubb38\ud5cc<\/h2>\n
\ub2e4\uc74c\uc740 \ubcf8 \uac15\uc88c\uc5d0\uc11c \uc0ac\uc6a9\ub41c \uc8fc\uc694 \ucc38\uace0 \ubb38\ud5cc\uc785\ub2c8\ub2e4:<\/p>\n
\n- Wavelet Theory and Applications, 2010<\/li>\n
- Machine Learning for Trading, 2016<\/li>\n
- Deep Learning for Time Series Forecasting, 2019<\/li>\n<\/ul>\n
<\/body><\/p>\n","protected":false},"excerpt":{"rendered":"
\ub370\uc774\ud130 \uacfc\ud559 \ubd84\uc57c\uc5d0\uc11c\ub294 \ub2e4\uc591\ud55c \ubc29\ubc95\ub860\uc774 \uc0ac\uc6a9\ub418\uace0 \uc788\uc73c\uba70, \uba38\uc2e0\ub7ec\ub2dd \ubc0f \ub525\ub7ec\ub2dd \uae30\uc220\uc740 \ud2b9\ud788 \uae08\uc735 \ubd84\uc57c\uc5d0\uc11c \uc790\ub3d9\ud654\ub41c \ud2b8\ub808\uc774\ub529 \uc2dc\uc2a4\ud15c \uac1c\ubc1c\uc5d0 \ub9ce\uc774 \ud65c\uc6a9\ub418\uace0 \uc788\uc2b5\ub2c8\ub2e4. \uc774\ub7ec\ud55c \uc2dc\uc2a4\ud15c\uc740 \uc7a1\uc74c \ub370\uc774\ud130\uc5d0\uc11c \uc720\uc758\ubbf8\ud55c \ud328\ud134\uc744 \ucd94\ucd9c\ud574\uc57c \ud558\uba70, \uc774\ub97c \uc704\ud574\uc11c\ub294 \ub370\uc774\ud130 \uc804\ucc98\ub9ac\uac00 \ud544\uc218\uc801\uc785\ub2c8\ub2e4. \ubcf8 \uac15\uc88c\uc5d0\uc11c\ub294 \uc6e8\uc774\ube14\ub9bf \ubcc0\ud658\uc744 \uc0ac\uc6a9\ud558\uc5ec \uc7a1\uc74c \ub370\uc774\ud130\ub97c \uc804\ucc98\ub9ac\ud558\ub294 \uc811\uadfc \ubc29\uc2dd\uc5d0 \ub300\ud574 \uc2ec\ub3c4 \uae4a\uc740 \ub17c\uc758\ub97c \uc9c4\ud589\ud558\uaca0\uc2b5\ub2c8\ub2e4. 1. \uba38\uc2e0\ub7ec\ub2dd\uacfc \ub525\ub7ec\ub2dd\uc758 \uae30\ucd08 \uba38\uc2e0\ub7ec\ub2dd\uc740 \ub370\uc774\ud130\ub97c … \ub354 \ubcf4\uae30 “\uba38\uc2e0\ub7ec\ub2dd \ubc0f \ub525\ub7ec\ub2dd \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529, \uc6e8\uc774\ube14\ub9bf\uc744 \uc774\uc6a9\ud55c \uc7a1\uc74c \ub370\uc774\ud130\uc758 \uc804\ucc98\ub9ac \ubc29\ubc95”<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[29],"tags":[],"class_list":["post-29221","post","type-post","status-publish","format-standard","hentry","category-29"],"yoast_head":"\n\uba38\uc2e0\ub7ec\ub2dd \ubc0f \ub525\ub7ec\ub2dd \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529, \uc6e8\uc774\ube14\ub9bf\uc744 \uc774\uc6a9\ud55c \uc7a1\uc74c \ub370\uc774\ud130\uc758 \uc804\ucc98\ub9ac \ubc29\ubc95 - 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