데이터분석/R76 [ADP] 시계열분석 (Time Series Analysis) > # 03. 시계열분석 (Time Series Analysis) > > # 1. 차분 및 Box-Cox 변환 > > > data("AirPassengers") > head(AirPassengers) [1] 112 118 132 129 121 135 > > par(mfrow=c(2,2)) > plot(AirPassengers, main = "Air Passengers") > plot(diff(AirPassengers), main = "Difference - Air Passenger") > > library(forecast) > > lambda lambda [1] -0.2947156 > new > plot(new, main = "Box Cox - Air Passengers") > plot(diff(new).. 2022. 1. 15. [ADP] 주성분분석(PCA, Principal Component Analysis) > # 02. 주성분분석 (PCA, Principal Component Analysis) > > # 2. 분석결과 해석 > > library(datasets) > data("USArrests") > head(USArrests) Murder Assault UrbanPop Rape Alabama 13.2 236 58 21.2 Alaska 10.0 263 48 44.5 Arizona 8.1 294 80 31.0 Arkansas 8.8 190 50 19.5 California 9.0 276 91 40.6 Colorado 7.9 204 78 38.7 > > fit1 summary(fit1) Importance of components: PC1 PC2 PC3 PC4 Standard deviation 1.5749 0.. 2022. 1. 15. [ADP] 정규화 모델 > # 01. 정규화 모델 [릿지(Ridge), 라쏘(Lasso), 엘라스틱넷(ElasticNet)] > > # 1. 정규화 개념 > > library(ridge) > > data("longley") > head(longley) GNP.deflator GNP Unemployed Armed.Forces Population Year Employed 1947 83.0 234.289 235.6 159.0 107.608 1947 60.323 1948 88.5 259.426 232.5 145.6 108.632 1948 61.122 1949 88.2 258.054 368.2 161.6 109.773 1949 60.171 1950 89.5 284.599 335.1 165.0 110.929 1950 61.187 1951.. 2022. 1. 15. [ADP] 그래프 작성 > ## 3장. 시각화 구현 > # 02. 분석 도구를 이용한 시각화 구현 : R > > # 1. 그래프 작성 > > > # 1) XY 그래프 > > library(ggplot2) > > data("ChickWeight") > head(ChickWeight) Grouped Data: weight ~ Time | Chick weight Time Chick Diet 1 42 0 1 1 2 51 2 1 1 3 59 4 1 1 4 64 6 1 1 5 76 8 1 1 6 93 10 1 1 > > ggplot(ChickWeight, aes(x=Time, y=weight, colour=Diet, group=Chick)) + geom_line() > # 결과를 보면 먹이별로 체중 변화를 보여주지만, 어느 먹이(Diet.. 2022. 1. 15. 이전 1 ··· 10 11 12 13 다음
