{"id":2036,"date":"2019-10-27T20:26:49","date_gmt":"2019-10-27T11:26:49","guid":{"rendered":"http:\/\/141.164.34.82\/?p=2036"},"modified":"2019-10-28T05:58:50","modified_gmt":"2019-10-27T20:58:50","slug":"manual-regression","status":"publish","type":"post","link":"http:\/\/ds.sumeun.org\/?p=2036","title":{"rendered":"Manual Regression"},"content":{"rendered":"

\uc190\uc218 \ud68c\uadc0\uace1\uc120\uc744 \uadf8\ub9ac\ub294 \ubc29\ubc95<\/h2>\n
genData=function(n=1000) {\n  #n <- 1000\n  x <- runif(n, -3, 3)\n  e <- rnorm(n, 0, 1.1)\n  y <- -0.3*x^2 + 1.4*x+ e\n  return(data.frame(x=x, y=y))\n}\n<\/code><\/pre>\n
dat <- genData(n=1000)\nplot(y~x, data=dat)\n<\/code><\/pre>\n
\"plot<\/p>\n
\uc0ac\ub78c\ub4e4\uc740 \uc5ec\ub7ec \uac00\uc9c0 ML\/AI\uac00 \ubb54\uac00 \uc2e0\ube44\uc2a4\ub85c\uc6b4 \ud798\uc774 \uc788\ub2e4\uace0 \uc0dd\uac01\ud55c\ub2e4. \ud558\uc9c0\ub9cc \uc801\uc5b4\ub3c4 \uc9c0\ub3c4 \ud559\uc2b5(supervised learnign)\uc758 \ud68c\uadc0(regression)\ub294 (\uac04\ub2e8\ud558\uac8c \uc815\ub9ac\ud558\uba74) \ub370\uc774\ud130\uc758 \ud06c\uae30\uc640 \uc801\uc808\ud55c \uc0ac\uc804 \uc9c0\uc2dd\uc758 \uacb0\ud569\uc73c\ub85c \uc124\uba85\ud560 \uc218 \uc788\ub2e4.<\/p>\n
\uc608\ub97c \ub4e4\uc5b4 \uc704\uc758 \ub370\uc774\ud130\ub97c \ubcf4\uc790. \\(x\\) \uac00 \uc8fc\uc5b4\uc84c\uc744 \ub54c, \\(y\\) \ub97c \uc608\uce21\ud558\ub824\uace0 \ud55c\ub2e4\uba74, \uac00\uc7a5 \uc190\uc26c\uc6b4 \ubc29\ubc95\uc740 \ub370\uc774\ud130\uc5d0\uc11c \\(x\\) \uc8fc\uc704\uc758 \\(y\\) \uc758 \ub300\ud45c\uac12\uc744 \uacc4\uc0b0\ud558\ub294 \uac83\uc774\ub2e4.<\/p>\n
\uc608\ub97c \ub4e4\uc5b4 \\(x=1\\) \uc5d0\uc11c \\(y\\) \ub97c \uc608\uce21\ud558\uace0\uc790 \ud55c\ub2e4\uba74, \\(0 < x < 1\\) \uc778 \ub370\uc774\ud130\uc5d0 \ub300\ud574 \\(y\\) \uc758 \ud3c9\uade0\uac12\uc744 \uc81c\uc2dc\ud558\ub294 \ubc29\ubc95\uc744 \uc0ac\uc6a9\ud560 \uc218 \uc788\ub2e4. <\/p>\n
predict2 <- function(dat, x, binsize=1) {\n  predy <- rep(NA, length(x))\n  for (i in seq_along(x)) {\n    x0 <- x[i]\n    xs <- dat[, "x"]\n    ys <- dat[, "y"]\n    ys <- ys[xs > x0-binsize & xs < x0+binsize]\n    predy[i] <- mean(ys, na.rm=TRUE)\n  }\n  return(predy)\n}\n<\/code><\/pre>\n
xs <- seq(-3,3,0.1)\ndatGG <- data.frame(x=xs, y=predict2(dat, x=xs, binsize=1))\nggplot(dat, aes(x=x, y=y)) + \n  geom_point(fill='grey70', col='grey20', alpha=0.2) + \n  geom_line(data=datGG, aes(x=x, y=y), size=1.1)  \n<\/code><\/pre>\n
\"plot<\/p>\n
\uacb0\uacfc\ub294 \uc704\uc640 \uac19\ub2e4. \ubb3c\ub860 \uc0ac\ub78c\uc774 \uc9c1\uc811 \uacc4\uc0b0\ud558\ub824\uba74 \uc2dc\uac04\uc774 \ub9ce\uc774 \uac78\ub9ac\uaca0\uc9c0\ub9cc, \uc2dc\uac04\ub9cc \uc788\ub2e4\uba74 \uc190\uc218 \uacc4\uc0b0\ud560 \uc218 \uc788\ub2e4. <\/p>\n
\uc774\ub54c \\(x = 1\\) \uc758 \uc608\uce21\uac12\uc744 \uad6c\ud558\uae30 \uc704\ud574\uc11c \uc0ac\uc6a9\ud558\ub294 \ub370\uc774\ud130\uc758 \\(x\\) \ubc94\uc704\uc640 \\(y\\) \uc608\uce21\uac12\uc744 \uad6c\ud560 \ub54c \uc0ac\uc6a9\ud558\ub294 \ubc29\ubc95(\ud3c9\uade0, \uc911\uc559\uac12, \uadf8 \ubc16\uc758 \ud568\uc218\ub4e4)\uc5d0 \ub530\ub77c \uc628\uac16 \ud68c\uadc0 \ubaa8\ud615(Kernel Regression \ub4f1)\uc774 \ub9cc\ub4e4\uc5b4 \uc9c8 \uc218 \uc788\uc9c0\ub9cc \ud575\uc2ec\uc740 \ube44\uc2b7\ud558\ub2e4.<\/p>\n
\uc608\ub97c \ub4e4\uc5b4 \\(x=1\\) \uc758 \uc608\uce21\uac12\uc744 \uad6c\ud558\uae30 \uc704\ud574 \\(-1 < x < 3\\) \ub97c \uc0ac\uc6a9\ud558\uac70\ub098,<\/p>\n
datGG <- data.frame(x=xs, y=predict2(dat, x=xs, binsize=2))\nggplot(dat, aes(x=x, y=y)) + \n  geom_point(fill='grey70', col='grey20', alpha=0.2) + \n  geom_line(data=datGG, aes(x=x, y=y), size=1.1)\n<\/code><\/pre>\n
\"plot<\/p>\n
\\(0.5 < x < 1.5\\) \ub97c \uc0ac\uc6a9\ud560 \uc218 \uc788\ub2e4.<\/p>\n
datGG <- data.frame(x=xs, y=predict2(dat, x=xs, binsize=0.5))\nggplot(dat, aes(x=x, y=y)) + \n  geom_point(fill='grey70', col='grey20', alpha=0.2) + \n  geom_line(data=datGG, aes(x=x, y=y), size=1.1)\n<\/code><\/pre>\n
\"plot<\/p>\n
(\uc774 \uacb0\uacfc\ub97c \ubcf4\uba74 \uc190\uc27d\uac8c \\(y\\) \uc608\uce21\uac12\uc744 \uad6c\ud558\uae30 \uc704\ud574 \uc0ac\uc6a9\ud558\ub294 \\(x\\) \uc758 \ubc94\uc704\ub97c \\(f(x)\\) \uc758 \uae30\uc6b8\uae30\uc5d0 \ub530\ub77c \uc870\uc808\ud574\uc57c\uaca0\ub2e4\ub294 \uc0dd\uac01\uc774 \ub5a0\uc624\ub974\uc9c0 \uc54a\ub294\uac00?)<\/strong><\/p>\n
\uc774\ub807\uac8c \ubcf4\uba74, \ub300\ubd80\ubd84\uc758 AI\/ML\uc740 \uc5b4\ucc98\uad6c\ub2c8\uc5c6\uc774 \uac04\ub2e8\ud558\ub2e4(\ubb3c\ub860 \uac1c\ub150\uc801<\/strong>\uc73c\ub85c \uac04\ub2e8\ud558\ub2e4\ub294 \uc598\uae30\uc774\ub2e4.) (\uc774\ub7f0 \uc774\uc720\ub85c Pearl\uc740 \ub300\ubd80\ubd84\uc758 ML\/AI\uac00 \ub2e8\uc21c\ud788 Curve Fitting\uc77c \ubfd0\uc774\ub77c\uace0 \ube44\ud558\ud55c\ub2e4.<\/a> \uc2ec\ub9ac\ud559\uc790\ub4e4\uc774 fMRI \uc5f0\uad6c\ub97c \ub1cc \uc0ac\uc9c4 \ucc0d\uae30\uc5d0 \ubd88\uacfc\ud558\ub2e4\uace0 \ube44\uc544\ub0e5\uac70\ub9ac\ub358 \uac83\uacfc \ube44\uc2b7\ud55c \ub4ef?)<\/p>\n
\uc774 \ubc29\ubc95\uc740 \uc5ec\ub7ec \uc785\ub825 \ubcc0\uc218\uc5d0 \ub300\ud574\uc11c\ub3c4 \uc801\uc6a9 \uac00\ub2a5\ud558\ub2e4. \ubb3c\ub860 \ubcc0\uc218\uc758 \uac2f\uc218\uac00 \ub298\uc5b4\ub0a0 \uc218\ub85d \ub370\uc774\ud130\uc758 \uac2f\uc218\ub294 \uad49\uc7a5\ud788 \ub298\uc5b4\ub098\uae30 \ub54c\ubb38\uc5d0 \uc0ac\uc804 \uc9c0\uc2dd<\/strong>\uc744 \ud65c\uc6a9\ud558\uac8c \ub41c\ub2e4. \uc774\ub54c \uc0ac\uc804\uc9c0\uc2dd<\/strong>\uc740 \ubcf4\ud1b5 \ubaa8\ud615<\/strong>(\ud639\uc740 \ubca0\uc774\uc9c0\uc548\uc5d0\uc11c \uc0ac\uc804 \ubd84\ud3ec)\uc73c\ub85c \ub098\ud0c0\ub09c\ub2e4.<\/p>\n
\uc785\ub825\ubcc0\uc218\uc77c \ub54c \uc608\uc2dc.<\/h3>\n
genData2=function(n=1000) {\n  #n <- 1000\n  x1 <- runif(n, -3, 3)\n  x2 <- runif(n, -3, 3)\n  e <- rnorm(n, 0, 1.1)\n  y <- -0.3*x1^2 + 2*sin(x2)*x1 + 1.4*x1+ e\n  return(data.frame(x1=x1, x2=x2, y=y))\n}\n<\/code><\/pre>\n
library(plot3D)\ndat <- genData2(n=1000)\nscatter3D(x=dat$x1, y=dat$x2, z=dat$y)\n<\/code><\/pre>\n
\"plot<\/p>\n
#install.packages('plot3Drgl')\nlibrary(plot3Drgl)\n#scatter3Drgl(x=dat$x1, y=dat$x2, z=dat$y)\n<\/code><\/pre>\n
\ub9cc\uc57d \ub450 \ubcc0\uc218 \\(x_1\\) , \\(x_2\\) \ub85c \\(y\\) \ub97c \uc608\uce21\ud55c\ub2e4\uba74, \uc608\uce21\ud558\uace0\uc790 \ud558\ub294 \\(x_1\\) , \\(x_2\\) \uc8fc\ubcc0 \ub370\uc774\ud130\uc5d0\uc11c \\(y\\) \uc758 \ub300\ud45c\uac12\uc744 \uad6c\ud558\uba74 \ub41c\ub2e4. \uc608\ub97c \ub4e4\uc5b4, \\(x_1 = 1\\) , \\(x_2 = 1\\) \uc77c\ub54c \\(y\\) \ub97c \uc608\uce21\ud55c\ub2e4\uba74, \\(0 < x_1 < 2\\) \uc774\uace0 \\(0 < x_2 < 2\\) \uc778 \ub370\uc774\ud130\uc5d0 \ub300\ud574 \\(y\\) \ub97c \ud3c9\uade0\ud558\ub294 \ubc29\ubc95\uc744 \uc0dd\uac01\ud574 \ubcfc \uc218 \uc788\ub2e4. <\/p>\n
predict3 <- function(dat, x1, x2, binsize=1) {\n  stopifnot(length(x1)==length(x2))\n  predy <- rep(NA, length(x1))\n  for (i in seq_along(x1)) {\n    x10 <- x1[i]\n    x20 <- x2[i]\n    x1s <- dat[, "x1"]\n    x2s <- dat[, "x2"]\n    ys <- dat[, "y"]\n    ys <- ys[x1s > x10-binsize & x1s < x10+binsize &\n             x2s > x20-binsize & x2s < x20+binsize]\n    predy[i] <- mean(ys, na.rm=TRUE)\n  }\n  return(predy)\n}\n<\/code><\/pre>\n
datp <- expand.grid(x1=seq(-3,3,0.1), x2=seq(-3,3,0.1))\ndatp$y <- predict3(dat, x1=datp$x1, x2=datp$x2, binsize=1)\nscatter3D(x=datp$x1, y=datp$x2, z=datp$y)\n<\/code><\/pre>\n
\"plot<\/p>\n
#scatter3Drgl(x=datp$x1, y=datp$x2, z=datp$y)\n<\/code><\/pre>\n
datp$y <- predict3(dat, x1=datp$x1, x2=datp$x2, binsize=2)\nscatter3D(x=datp$x1, y=datp$x2, z=datp$y)\n<\/code><\/pre>\n
\"plot<\/p>\n
#scatter3Drgl(x=datp$x1, y=datp$x2, z=datp$y)\n<\/code><\/pre>\n
\ubd88\ud655\uc2e4\uc131<\/h2>\n
\ud558\uc9c0\ub9cc \uc774\ub7f0 \ub2e8\uc21c\ud55c \ubc29\ubc95\uc758 \ub610 \ud55c\uac00\uc9c0 \ubb38\uc81c\ub294 \uc774 \uacb0\uacfc\uac00 \uc5bc\ub9c8\ub098 \uc815\ud655\ud55c\uc9c0 \uc54c \uc218 \uc5c6\ub2e4\ub294 \uc810\uc774\ub2e4.<\/p>\n
\uc608\ub97c \ub4e4\uc5b4 100\uac1c\uc758 \ub370\uc774\ud130\ub97c \uc0ac\uc6a9\ud574\uc11c \ud68c\uadc0\uc120\uc744 \uad6c\uc131\ud560 \uc218\ub3c4 \uc788\uace0, 1000\uac1c\uc758 \ub370\uc774\ud130\ub97c \uc368\uc11c \ud68c\uadc0\uc120\uc744 \uad6c\uc131\ud560 \uc218\ub3c4 \uc788\ub2e4. \ud558\uc9c0\ub9cc \uc774 \ub458\uc774 \uc815\ud655\uc131\uc5d0\uc11c, \ub610\ub294 \uc2e0\ube59\uc131\uc5d0\uc11c \uc5bc\ub9c8\ub098 \ucc28\uc774\uac00 \ub098\ub294\uc9c0, \uc0ac\ub78c\ub4e4\uc740 \uc54c\uae30 \ud798\ub4e4\ub2e4. \ub2e8\uc9c0 \uc9c1\uad00\uc801\uc73c\ub85c \ucd94\uce21\ud560 \uc218 \uc788\uc744 \ubfd0\uc774\ub2e4. (\ud558\uc9c0\ub9cc \uc0ac\ub78c\ub9c8\ub2e4 \uc774 \ucd94\uce21\uc774 \ub2e4\ub974\ub2e4\ub294 \ubb38\uc81c\uac00 \uc788\ub2e4.)<\/p>\n
dat <- genData(n=100)\n\nxs <- seq(-3,3,0.1)\ndatGG <- data.frame(x=xs, y=predict2(dat, x=xs, binsize=1))\nggplot(dat, aes(x=x, y=y)) + \n  geom_point(col='grey20', alpha=0.2) + \n  geom_line(data=datGG, aes(x=x, y=y), size=1.1)  \n<\/code><\/pre>\n
\"plot<\/p>\n
dat <- genData(n=10000)\n\nxs <- seq(-3,3,0.1)\ndatGG <- data.frame(x=xs, y=predict2(dat, x=xs, binsize=1))\nggplot(dat, aes(x=x, y=y)) + \n  geom_point(col='grey20', alpha=0.2) + \n  geom_line(data=datGG, aes(x=x, y=y), size=1.1)  \n<\/code><\/pre>\n
\"plot<\/p>\n
(\uc774 \uacb0\uacfc\ub97c \ubcf4\ub2c8 \\(y\\) \uc608\uce21\uac12\uc744 \ub098\ud0c0\ub0b4\uae30 \uc704\ud574 \uc0ac\uc6a9\ud558\ub294 \\(x\\) \uc758 \ubc94\uc704\ub97c \ud45c\ubcf8\ud06c\uae30\uc5d0 \ub530\ub77c \uc801\uc808\ud788 \uc870\uc808\ud574\uc57c\uaca0\ub2e4\ub294 \uc544\uc774\ub514\uc5b4\uac00 \ub5a0\uc624\ub974\uc9c0 \uc54a\ub294\uac00?<\/strong> \ud45c\ubcf8\ud06c\uae30\uac00 \uc791\uc744 \uc218\ub85d, \uadf8\ub9ac\uace0 \uc0ac\uc6a9\ub41c \\(x\\) \uc758 \ubc94\uc704\uac00 \uc881\uc744 \uc218\ub85d \ubd84\uc0b0\uc774 \ucee4\uc9c0\ub2c8, \ub458 \uc911 \ud558\ub098\ub294 \ub298\ub824\uc57c \uc801\ub2f9\ud55c \ubd84\uc0b0\uc5d0 \uc801\ub2f9\ud55c \ud3b8\ud5a5\uc744 \uc5bb\uc744 \uc218 \uc788\ub2e4.)<\/p>\n
\ubd88\ud655\uc2e4\uc131\uc744 \ub300\ucc98\ud558\ub294 \ubc29\ubc95<\/h2>\n
\ud655\ub960\ubaa8\ud615\uc740 \uc774\ub7f0 \ubd88\ud655\uc2e4\uc131\uc744 \uae30\ubcf8\uc801\uc778 \ud655\ub960 \ubc95\uce59\uc744 \uc0ac\uc6a9\ud558\uc5ec \uacc4\uc0b0 \uac00\ub2a5\ud558\uac8c \ud574\uc900\ub2e4. \ud655\ub960\ubaa8\ud615\uacfc \ud655\ub960\ubc95\uce59\uc744 \ud1b5\ud574 \uc6b0\ub9ac\uac00 \uad00\uc2ec\uc774 \uc788\ub294 \ub300\uc0c1(\uc608. \uc608\uce21 \ud568\uc218)\uc5d0 \ub300\ud55c \ubd88\ud655\uc2e4\uc131(\ud655\ub960)\uc744 \uacc4\uc0b0\ud560 \uc218 \uc788\ub2e4. <\/p>\n
dat <- genData(n=100)\n\nlibrary(visreg) # install.packages('visreg')\n\nfitLM <- lm(y~x+I(x^2), data=dat)\nvisreg(fitLM, 'x')\n<\/code><\/pre>\n
\"plot<\/p>\n
dat <- genData(n=20)\n\nlibrary(visreg) # install.packages('visreg')\n\nfitLM <- lm(y~x+I(x^2), data=dat)\nvisreg(fitLM, 'x')\n<\/code><\/pre>\n
\"plot<\/p>\n
\uc704\uc758 \uadf8\ub798\ud504(\ud2b9\ud788 \uc2e0\ub8b0\uad6c\uac04)\ub294 \ub9cc\uc57d \ubaa8\ud615\uc774 \uc815\ud655\ud558\ub2e4\uba74<\/strong>, \ub2e8\uc9c0 20\uac1c\uc758 \uc790\ub8cc\ub9cc\uc73c\ub85c\ub3c4 \\(f(x)\\) \ub97c \uaf64\ub098 \uc815\ud655\ud558\uac8c \uad6c\uc131\ud560 \uc218 \uc788\uc74c\uc744 \ubcf4\uc5ec\uc900\ub2e4.[2]<\/sup><\/p>\n
[2]:<\/sup> \ud3b8\uc758\uc0c1 \uac04\ub2e8\ud558\uac8c \ub9d0\ud558\uc790\uba74, \\(f(x)\\) \uac00 \\(a x^2 + bx+c\\) \uc774\uace0, \uc624\ucc28\uac00 \uc815\uaddc\ubd84\ud3ec\ub97c \ub530\ub974\uace0, \ub4f1\ubd84\uc0b0\uc774\uace0, \uc624\ucc28\uc790\uae30\uc0c1\uad00\uc774 \uc5c6\uc73c\uba70… \ubb3c\ub860 \uc815\ud655\uc131\uc758 \uae30\uc900\ub3c4 \uc815\ud574\uc57c \uaca0\uc9c0\ub9cc…<\/p>\n
\uae00\uc744 \uc4f0\uace0 \ubcf4\ub2c8, \uc758\uc0ac\uacb0\uc815\ub098\ubb34\uc640 \uac19\uc740 \uc54c\uace0\ub9ac\uc998\uc801 \ubc29\ubc95\uc744 \uae4c\ub294 \uae00\uc774 \ub41c \ub4ef \ud558\uc9c0\ub9cc, \uc758\uc0ac\uacb0\uc815\ub098\ubb34\ub3c4 CV(Cross Validation; \uad50\ucc28\uac80\uc99d)\ub098, \ubd93\uc2a4\ud2b8\ub7a9\uc744 \uc0ac\uc6a9\ud558\uc5ec, \ucd5c\uc885\ubaa8\ud615\uc758 \ubd88\ud655\uc2e4\uc131\uc744 \uce21\uc815\ud560 \uc218 \uc788\ub2e4. <\/p>\n","protected":false},"excerpt":{"rendered":"
\uc190\uc218 \ud68c\uadc0\uace1\uc120\uc744 \uadf8\ub9ac\ub294 \ubc29\ubc95 genData=function(n=1000) { #n <- 1000 x <- runif(n, -3, 3) e <- rnorm(n, 0, 1.1) y <- -0.3*x^2 + 1.4*x+ e return(data.frame(x=x, y=y)) } dat <- genData(n=1000) plot(y~x, data=dat) \uc0ac\ub78c\ub4e4\uc740 \uc5ec\ub7ec \uac00\uc9c0 ML\/AI\uac00 \ubb54\uac00 \uc2e0\ube44\uc2a4\ub85c\uc6b4 \ud798\uc774 \uc788\ub2e4\uace0 \uc0dd\uac01\ud55c\ub2e4. \ud558\uc9c0\ub9cc \uc801\uc5b4\ub3c4 \uc9c0\ub3c4 \ud559\uc2b5(supervised learnign)\uc758 \ud68c\uadc0(regression)\ub294 (\uac04\ub2e8\ud558\uac8c \uc815\ub9ac\ud558\uba74) \ub370\uc774\ud130\uc758 \ud06c\uae30\uc640 \uc801\uc808\ud55c \uc0ac\uc804 \uc9c0\uc2dd\uc758 […]<\/p>\n","protected":false},"author":1,"featured_media":2039,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[371,146,319],"tags":[412,410,338,409,411,408],"jetpack_featured_media_url":"http:\/\/ds.sumeun.org\/wp-content\/uploads\/2019\/10\/manual_regression.png","_links":{"self":[{"href":"http:\/\/ds.sumeun.org\/index.php?rest_route=\/wp\/v2\/posts\/2036"}],"collection":[{"href":"http:\/\/ds.sumeun.org\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/ds.sumeun.org\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/ds.sumeun.org\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"http:\/\/ds.sumeun.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=2036"}],"version-history":[{"count":6,"href":"http:\/\/ds.sumeun.org\/index.php?rest_route=\/wp\/v2\/posts\/2036\/revisions"}],"predecessor-version":[{"id":2043,"href":"http:\/\/ds.sumeun.org\/index.php?rest_route=\/wp\/v2\/posts\/2036\/revisions\/2043"}],"wp:featuredmedia":[{"embeddable":true,"href":"http:\/\/ds.sumeun.org\/index.php?rest_route=\/wp\/v2\/media\/2039"}],"wp:attachment":[{"href":"http:\/\/ds.sumeun.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=2036"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/ds.sumeun.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=2036"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/ds.sumeun.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=2036"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}