\n
\uc548\ub155\ud558\uc138\uc694! \uc774\ubc88 \ud3ec\uc2a4\ud305\uc5d0\uc11c\ub294 \uba38\uc2e0\ub7ec\ub2dd\uacfc \ub525\ub7ec\ub2dd\uc744 \ud65c\uc6a9\ud55c \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529\uc744 \ub2e4\ub8e8\uba70, \ud2b9\ud788 statsmodels<\/code> \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \uc774\uc6a9\ud55c \uc120\ud615 \ud68c\uadc0 \ubd84\uc11d(Ordinary Least Squares, OLS)\uc5d0 \ub300\ud574 \uc790\uc138\ud788 \uc124\uba85\ud558\uaca0\uc2b5\ub2c8\ub2e4.<\/p>\n\ud000\ud2b8 \ub9e4\ub9e4\ub294 \ub370\uc774\ud130 \uae30\ubc18\uc758 \ud22c\uc790 \uc804\ub7b5 \uc218\ub9bd\uc744 \ud1b5\ud574 \uc774\uc775\uc744 \uadf9\ub300\ud654\ud558\ub294 \uac83\uc744 \ubaa9\ud45c\ub85c \ud569\ub2c8\ub2e4. \uba38\uc2e0\ub7ec\ub2dd\uacfc \ub525\ub7ec\ub2dd \uae30\ubc95\uc740 \ubc29\ub300\ud55c \uc591\uc758 \ub370\uc774\ud130\ub97c \ucc98\ub9ac\ud558\uace0 \uc774\ub97c \uae30\ubc18\uc73c\ub85c \uc608\uce21 \ubc0f \ud310\ub2e8\uc744 \uc790\ub3d9\ud654\ud568\uc73c\ub85c\uc368 \ud22c\uc790 \uacb0\uc815\uc744 \ub3c4\uc640\uc90d\ub2c8\ub2e4.<\/p>\n<\/div>\n
\n
1. \uc120\ud615 \ud68c\uadc0 \ubd84\uc11d\uc758 \uc774\ud574<\/h2>\n
\uc120\ud615 \ud68c\uadc0 \ubd84\uc11d\uc740 \uc885\uc18d \ubcc0\uc218\uc640 \ud55c \uac1c \uc774\uc0c1\uc758 \ub3c5\ub9bd \ubcc0\uc218 \uac04\uc758 \uc120\ud615 \uad00\uacc4\ub97c \ubaa8\ub378\ub9c1\ud558\ub294 \ud1b5\uacc4 \uae30\ubc95\uc785\ub2c8\ub2e4. \ud68c\uadc0 \ubd84\uc11d\uc744 \ud1b5\ud574 \uc6b0\ub9ac\ub294 \ub370\uc774\ud130\ub97c \uae30\ubc18\uc73c\ub85c \ubcc0\uc218 \uac04\uc758 \uad00\uacc4\ub97c \uc774\ud574\ud558\uace0, \ubbf8\ub798\uc758 \uac12\uc744 \uc608\uce21\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n
\uc120\ud615 \ud68c\uadc0\uc758 \uae30\ubcf8 \ubc29\uc815\uc2dd\uc740 \ub2e4\uc74c\uacfc \uac19\uc2b5\ub2c8\ub2e4:<\/p>\n
Y = \u03b20 + \u03b21X1 + \u03b22X2 + ... + \u03b2nXn + \u03b5<\/code><\/p>\n\uc5ec\uae30\uc11c Y<\/code>\ub294 \uc885\uc18d \ubcc0\uc218, X1, X2, ..., Xn<\/code>\uc740 \ub3c5\ub9bd \ubcc0\uc218, \u03b20<\/code>\ub294 \uc808\ud3b8, \u03b21, \u03b22, ..., \u03b2n<\/code>\uc740 \uac01\uac01\uc758 \uacc4\uc218, \u03b5<\/code>\ub294 \uc624\ucc28(term)\uc785\ub2c8\ub2e4.<\/p>\n\uc6b0\ub9ac\ub294 OLS \ubc29\ubc95\uc744 \uc0ac\uc6a9\ud558\uc5ec \uc774 \uacc4\uc218\ub97c \ucd94\uc815\ud569\ub2c8\ub2e4. OLS\ub294 \uc624\ucc28 \uc81c\uacf1\ud569\uc744 \ucd5c\uc18c\ud654\ud558\ub294 \ubc29\ubc95\uc785\ub2c8\ub2e4.<\/p>\n<\/div>\n
\n
2. statsmodels \ub77c\uc774\ube0c\ub7ec\ub9ac \uc18c\uac1c<\/h2>\n
statsmodels<\/code>\ub294 \ud30c\uc774\uc36c\uc5d0\uc11c \ud1b5\uacc4 \ubaa8\ub378 \ubc0f \ud68c\uadc0 \ubd84\uc11d\uc744 \uc218\ud589\ud558\uae30 \uc704\ud55c \uac15\ub825\ud55c \ub77c\uc774\ube0c\ub7ec\ub9ac\uc785\ub2c8\ub2e4. \uc774 \ub77c\uc774\ube0c\ub7ec\ub9ac\ub294 \uc77c\ubc18\uc801\uc778 \ud68c\uadc0 \ubd84\uc11d, \uc2dc\uacc4\uc5f4 \ubd84\uc11d, \uc0dd\uc874 \ubd84\uc11d \ub4f1\uc758 \ub2e4\uc591\ud55c \ud1b5\uacc4 \ubaa8\ub378\uc744 \uc81c\uacf5\ud569\ub2c8\ub2e4.<\/p>\n\ud2b9\ud788 OLS \ud68c\uadc0 \ubd84\uc11d\uc744 \uc218\ud589\ud558\ub294\ub370 \ub9e4\uc6b0 \uc720\uc6a9\ud558\uba70, \ubaa8\ub378\uc744 \uc801\ud569(fit)\ud55c \ud6c4 \uacb0\uacfc\ub97c \ud574\uc11d\ud558\ub294 \ub2e4\uc591\ud55c \uae30\ub2a5\uc744 \uc81c\uacf5\ud569\ub2c8\ub2e4.<\/p>\n<\/div>\n
\n
3. \ub370\uc774\ud130 \uc900\ube44<\/h2>\n
\ub370\uc774\ud130\ub294 \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529\uc758 \ud575\uc2ec \uc694\uc18c\uc785\ub2c8\ub2e4. \ud22c\uc790 \ubd84\uc11d\uac00\ub098 \ud2b8\ub808\uc774\ub354\ub294 \uc77c\ubc18\uc801\uc73c\ub85c \uc7ac\ubb34 \ub370\uc774\ud130, \uc8fc\uac00 \ub370\uc774\ud130, \uc2dc\uc7a5 \uc9c0\ud45c \ub4f1\uc744 \uc0ac\uc6a9\ud569\ub2c8\ub2e4. \uc774\ubc88 \uc608\uc81c\uc5d0\uc11c\ub294 \uc8fc\uac00 \ub370\uc774\ud130\ub97c \uc0ac\uc6a9\ud55c \uc120\ud615 \ud68c\uadc0 \ubd84\uc11d\uc744 \uc9c4\ud589\ud558\uaca0\uc2b5\ub2c8\ub2e4.<\/p>\n
\ub370\uc774\ud130\ub97c \uc900\ube44\ud558\uae30 \uc704\ud574\uc11c\ub294 pandas<\/code> \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \uc0ac\uc6a9\ud558\uc5ec CSV \ud30c\uc77c \ud615\uc2dd\uc73c\ub85c \ub370\uc774\ud130\ub97c \ubd88\ub7ec\uc62c \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ub2e4\uc74c\uc740 \ub370\uc774\ud130 \ubd88\ub7ec\uc624\uae30\uc640 \uae30\ubcf8\uc801\uc778 \ub370\uc774\ud130 \uc804\ucc98\ub9ac \uacfc\uc815\uc785\ub2c8\ub2e4:<\/p>\nimport pandas as pd\n\n# \ub370\uc774\ud130 \ubd88\ub7ec\uc624\uae30\ndata = pd.read_csv('stock_data.csv')\n\n# \ub370\uc774\ud130\uc758 \uccab 5\ud589 \ucd9c\ub825\nprint(data.head())<\/code><\/pre>\n<\/div>\n\n
4. OLS \ud68c\uadc0 \ubd84\uc11d \uc218\ud589<\/h2>\n
\ub370\uc774\ud130\uac00 \uc900\ube44\ub418\uba74 OLS \ud68c\uadc0 \ubd84\uc11d\uc744 \uc218\ud589\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. statsmodels<\/code> \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \ud65c\uc6a9\ud558\uc5ec \ubaa8\ub378\uc744 \uc0dd\uc131\ud558\uace0 \uc801\ud569\ud558\ub294 \uacfc\uc815\uc740 \ub2e4\uc74c\uacfc \uac19\uc2b5\ub2c8\ub2e4:<\/p>\nimport statsmodels.api as sm\n\n# \uc885\uc18d \ubcc0\uc218\uc640 \ub3c5\ub9bd \ubcc0\uc218 \uc124\uc815\nX = data['Independent_Variable']\nY = data['Dependent_Variable']\n\n# \uc0c1\uc218\ud56d \ucd94\uac00\nX = sm.add_constant(X)\n\n# OLS \ubaa8\ub378 \uc801\ud569\nmodel = sm.OLS(Y, X).fit()\n\n# \uacb0\uacfc \ucd9c\ub825\nprint(model.summary())<\/code><\/pre>\n\uc774 \ucf54\ub4dc\ub294 \uc758\uc874 \ubcc0\uc218\uc640 \ub3c5\ub9bd \ubcc0\uc218\ub97c \uc124\uc815\ud558\uace0, OLS \ubaa8\ub378\uc744 \uc801\ud569\ud55c \ud6c4 \uadf8 \uacb0\uacfc\ub97c \uc694\uc57d\ud558\uc5ec \ucd9c\ub825\ud569\ub2c8\ub2e4. \ubaa8\ub378 \uc694\uc57d\uc5d0\ub294 \ud68c\uadc0 \uacc4\uc218, \ud45c\uc900 \uc624\ucc28, p-value, R-squared \uac12 \ub4f1\uc774 \ud3ec\ud568\ub418\uc5b4 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n<\/div>\n
\n
5. \ud68c\uadc0 \uacb0\uacfc \ud574\uc11d<\/h2>\n
OLS \ud68c\uadc0 \ubaa8\ub378\uc758 \uacb0\uacfc\ub294 \uc5ec\ub7ec \uac00\uc9c0 \ubc29\uc2dd\uc73c\ub85c \ud574\uc11d\ub420 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uac00\uc7a5 \uc911\uc694\ud55c \ud56d\ubaa9\uc740 \ub2e4\uc74c\uacfc \uac19\uc2b5\ub2c8\ub2e4:<\/p>\n
\n- \ud68c\uadc0 \uacc4\uc218 (Coefficients):<\/strong> \uac01 \ub3c5\ub9bd \ubcc0\uc218\uac00 \uc885\uc18d \ubcc0\uc218\uc5d0 \ubbf8\uce58\ub294 \uc601\ud5a5\uc744 \ub098\ud0c0\ub0c5\ub2c8\ub2e4.<\/li>\n
- R-squared:<\/strong> \ubaa8\ub378\uc774 \ub370\uc774\ud130\uc758 \ubcc0\ub3d9\uc131\uc744 \uc5bc\ub9c8\ub098 \uc124\uba85\ud558\ub294\uc9c0\ub97c \ub098\ud0c0\ub0b4\ub294 \uc9c0\ud45c\uc785\ub2c8\ub2e4. 1\uc5d0 \uac00\uae4c\uc6b8\uc218\ub85d \uc88b\uc740 \ubaa8\ub378\uc785\ub2c8\ub2e4.<\/li>\n
- p-value:<\/strong> \ud68c\uadc0 \uacc4\uc218\uac00 0\uc774 \uc544\ub2d0 \ud655\ub960\uc744 \ub098\ud0c0\ub0c5\ub2c8\ub2e4. \uc77c\ubc18\uc801\uc73c\ub85c 0.05 \uc774\ud558\uc77c \uacbd\uc6b0 \ud1b5\uacc4\uc801\uc73c\ub85c \uc720\uc758\ubbf8\ud558\ub2e4\uace0 \ud310\ub2e8\ud569\ub2c8\ub2e4.<\/li>\n<\/ul>\n<\/div>\n
\n
6. \uc794\ucc28 \ubd84\uc11d<\/h2>\n
\ucd5c\uc885\uc801\uc73c\ub85c, \ud68c\uadc0 \ubaa8\ub378\uc744 \ud3c9\uac00\ud558\uae30 \uc704\ud574 \uc794\ucc28\ub97c \ubd84\uc11d\ud558\ub294 \uac83\uc774 \uc911\uc694\ud569\ub2c8\ub2e4. \uc794\ucc28\ub294 \uc2e4\uc81c \uac12\uacfc \uc608\uce21 \uac12 \uac04\uc758 \ucc28\uc774\ub97c \ub098\ud0c0\ub0b4\uba70, \uc774\ub97c \ubd84\uc11d\ud568\uc73c\ub85c\uc368 \ubaa8\ub378\uc758 \uc801\ud569\uc131\uc744 \uac80\ud1a0\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n
import matplotlib.pyplot as plt\n\n# \uc794\ucc28 \uacc4\uc0b0\nresiduals = model.resid\n\n# \uc794\ucc28 \uc2dc\uac01\ud654\nplt.figure(figsize=(10, 6))\nplt.scatter(model.fittedvalues, residuals)\nplt.axhline(0, color='red', linestyle='--')\nplt.title('\uc794\ucc28 \ubd84\uc11d')\nplt.xlabel('\uc608\uce21 \uac12')\nplt.ylabel('\uc794\ucc28')\nplt.show()<\/code><\/pre>\n<\/div>\n\n
7. \uba38\uc2e0\ub7ec\ub2dd \ubc0f \ub525\ub7ec\ub2dd\uc73c\ub85c \ud655\uc7a5<\/h2>\n
\uc120\ud615 \ud68c\uadc0 \ubd84\uc11d\uc740 \uba38\uc2e0\ub7ec\ub2dd\uc758 \uae30\ucd08\ub97c \ubcf4\uc5ec\uc8fc\ub294 \uac04\ub2e8\ud558\uc9c0\ub9cc \uac15\ub825\ud55c \uae30\uc220\uc785\ub2c8\ub2e4. \uadf8\ub7ec\ub098 \uc2dc\uc7a5\uc758 \ubcf5\uc7a1\uc131\uc73c\ub85c \uc778\ud574 \ube44\uc120\ud615 \uad00\uacc4\ub97c \ubaa8\ub378\ub9c1\ud558\ub294 \uac83\ub3c4 \uc911\uc694\ud569\ub2c8\ub2e4. \uc774\ub97c \uc704\ud574 \uacb0\uc815 \ud2b8\ub9ac, \ub79c\ub364 \ud3ec\ub808\uc2a4\ud2b8, \uc2e0\uacbd\ub9dd \ub4f1 \ub2e4\uc591\ud55c \uba38\uc2e0\ub7ec\ub2dd \uc54c\uace0\ub9ac\uc998\uacfc \ubaa8\ub378\uc744 \uc0ac\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n
\uc608\ub97c \ub4e4\uc5b4, \uc2e0\uacbd\ub9dd\uc744 \ud65c\uc6a9\ud55c \ub525\ub7ec\ub2dd\uc5d0\uc11c\ub294 \uc5ec\ub7ec \uce35\uc744 \uc313\uc740 \ubaa8\ub378\ub85c \ube44\uc120\ud615\uc131\uc744 \ud559\uc2b5\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. Keras\uc640 TensorFlow\uc640 \uac19\uc740 \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \ud1b5\ud574 \uad6c\ud604\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n<\/div>\n
\n
8. \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529 \uc804\ub7b5 \uc218\ub9bd<\/h2>\n
\uc774\uc81c \uc6b0\ub9ac\ub294 OLS \ud68c\uadc0 \ubd84\uc11d\uc744 \ud1b5\ud574 \uc5bb\uc740 \uc9c0\uc2dd\uc744 \ubc14\ud0d5\uc73c\ub85c \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529 \uc804\ub7b5\uc744 \uc218\ub9bd\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uae30\ubcf8\uc801\uc778 \uc804\ub7b5\uc740 \uc544\ub798\uc640 \uac19\uc2b5\ub2c8\ub2e4:<\/p>\n
\n- \uc2dc\uc7a5\uc5d0 \ub300\ud55c \uacfc\uac70 \ub370\uc774\ud130\ub97c \ubd84\uc11d\ud569\ub2c8\ub2e4.<\/li>\n
- OLS \ud68c\uadc0 \ubaa8\ub378\uc744 \uc0ac\uc6a9\ud558\uc5ec \uc608\uce21 \ubaa8\ub378\uc744 \uad6c\ucd95\ud569\ub2c8\ub2e4.<\/li>\n
- \uc608\uce21 \uacb0\uacfc\ub97c \uae30\ubc18\uc73c\ub85c \ub9e4\ub9e4 \uc2e0\ud638\ub97c \uc0dd\uc131\ud569\ub2c8\ub2e4.<\/li>\n
- \uc2e0\ud638\uc5d0 \ub530\ub77c \uac70\ub798\ub97c \uc2e4\ud589\ud569\ub2c8\ub2e4.<\/li>\n<\/ol>\n
\uc774 \uacfc\uc815\uc5d0\uc11c \uc870\uc815 \uac00\ub2a5\ud55c \ub9e4\uac1c\ubcc0\uc218\ub4e4(\uc608: \ub9e4\uc218\/\ub9e4\ub3c4 \uae30\uc900, \uc190\uc808\ub9e4 \ub4f1)\uc744 \uace0\ub824\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n<\/div>\n
\n
9. \uacb0\ub860<\/h2>\n
\uc774\ubc88 \ud3ec\uc2a4\ud305\uc5d0\uc11c\ub294 \uba38\uc2e0\ub7ec\ub2dd \ubc0f \ub525\ub7ec\ub2dd \uae30\uc220\uc744 \ud65c\uc6a9\ud55c \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529\uc758 \uccab\uac78\uc74c\uc73c\ub85c OLS \ud68c\uadc0 \ubd84\uc11d\uc744 \uc18c\uac1c\ud588\uc2b5\ub2c8\ub2e4. statsmodels<\/code> \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \ud1b5\ud574 \uc120\ud615 \ud68c\uadc0 \ubd84\uc11d\uc744 \uc218\ud589\ud558\uace0, \uadf8 \uacb0\uacfc\uc640 \ud574\uc11d\uc5d0 \ub300\ud574 \uc54c\uc544\ubcf4\uc558\uc2b5\ub2c8\ub2e4.<\/p>\n\uc2dc\uc7a5\uc5d0\uc11c\ub294 \ud56d\uc0c1 \ub2e4\uc591\ud55c \ubcc0\uc218\ub4e4\uc774 \uc601\ud5a5\uc744 \ubbf8\uce58\uace0 \uc788\uc73c\ubbc0\ub85c, \ub2e8\uc21c\ud55c \ubaa8\ub378\ubcf4\ub2e4\ub294 \uc880 \ub354 \ubcf5\uc7a1\ud55c \ubaa8\ub378\uacfc \ub370\uc774\ud130\ub97c \ud65c\uc6a9\ud558\ub294 \uac83\uc774 \uc911\uc694\ud569\ub2c8\ub2e4. \ub2e4\uc74c \ud3ec\uc2a4\ud305\uc5d0\uc11c\ub294 \ub2e4\ub978 \uba38\uc2e0\ub7ec\ub2dd \uae30\ubc95 \ubc0f \uc804\ub7b5\uc5d0 \ub300\ud574 \ub2e4\ub8e8\uc5b4\ubcf4\uaca0\uc2b5\ub2c8\ub2e4. \uac10\uc0ac\ud569\ub2c8\ub2e4!<\/p>\n<\/div>\n
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\uc548\ub155\ud558\uc138\uc694! \uc774\ubc88 \ud3ec\uc2a4\ud305\uc5d0\uc11c\ub294 \uba38\uc2e0\ub7ec\ub2dd\uacfc \ub525\ub7ec\ub2dd\uc744 \ud65c\uc6a9\ud55c \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529\uc744 \ub2e4\ub8e8\uba70, \ud2b9\ud788 statsmodels \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \uc774\uc6a9\ud55c \uc120\ud615 \ud68c\uadc0 \ubd84\uc11d(Ordinary Least Squares, OLS)\uc5d0 \ub300\ud574 \uc790\uc138\ud788 \uc124\uba85\ud558\uaca0\uc2b5\ub2c8\ub2e4. \ud000\ud2b8 \ub9e4\ub9e4\ub294 \ub370\uc774\ud130 \uae30\ubc18\uc758 \ud22c\uc790 \uc804\ub7b5 \uc218\ub9bd\uc744 \ud1b5\ud574 \uc774\uc775\uc744 \uadf9\ub300\ud654\ud558\ub294 \uac83\uc744 \ubaa9\ud45c\ub85c \ud569\ub2c8\ub2e4. \uba38\uc2e0\ub7ec\ub2dd\uacfc \ub525\ub7ec\ub2dd \uae30\ubc95\uc740 \ubc29\ub300\ud55c \uc591\uc758 \ub370\uc774\ud130\ub97c \ucc98\ub9ac\ud558\uace0 \uc774\ub97c \uae30\ubc18\uc73c\ub85c \uc608\uce21 \ubc0f \ud310\ub2e8\uc744 \uc790\ub3d9\ud654\ud568\uc73c\ub85c\uc368 \ud22c\uc790 \uacb0\uc815\uc744 \ub3c4\uc640\uc90d\ub2c8\ub2e4. 1. \uc120\ud615 \ud68c\uadc0 \ubd84\uc11d\uc758 … \ub354 \ubcf4\uae30 “\uba38\uc2e0\ub7ec\ub2dd \ubc0f \ub525\ub7ec\ub2dd \uc54c\uace0\ub9ac\uc998 \ud2b8\ub808\uc774\ub529, statsmodels\ub97c \uc0ac\uc6a9\ud55c \uc120\ud615 OLS \ud68c\uadc0 \ubd84\uc11d”<\/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-28754","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, statsmodels\ub97c \uc0ac\uc6a9\ud55c \uc120\ud615 OLS \ud68c\uadc0 \ubd84\uc11d - 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