6.2.1 Function components 6.2.2 Primitive functions 6.2.3 First-class functions 6.3 Function composition 6.4 Lexical scoping 6.4.1 Name masking 6.4.2 Functions versus variables 6.4.3 A fresh start 6.4.4 Dynamic
However, there are plot methods for many R objects, including functions, data.frames, density objects, etc. Use methods(plot) and the documentation for these. 这句话是说,要用plot画散点图,实际上调用的是plot.default函数,而对于R中许多其他对象,plot还有许多其他方法,用methods函数来查看 methods(...
convert_as_factor(), set_ref_level(), reorder_levels(): Provides pipe-friendly functions to convert simultaneously multiple variables into a factor variable. make_clean_names(): Pipe-friendly function to make syntactically valid column names (for input data frame) or names (for input vector)....
cor_select(): subset a correlation matrix by selecting variables of interest. pull_triangle(),pull_upper_triangle(),pull_lower_triangle(): pull upper and lower triangular parts of a (correlation) matrix. replace_triangle(),replace_upper_triangle(),replace_lower_triangle(): replace upper and lo...
set.seed(1)lmProfile2<-rfe(x,logBBB,sizes=c(2:25,30,35,40,45,50,55,60,65),rfeControl=rfeControl(functions=lmFuncs,rerank=TRUE,number=200))###模型之间的比较xyplot(lmProfile$results$RMSE+lmProfile2$results$RMSE~lmProfile$results$Variables,type=c("g","p","l"),auto.key=TRUE) ...
Rename variables and functions automatically in the MATLAB Editor. Published: 4 Feb 2012 Feedback Using Live Editor Tasks Using Live Editor Tasks(2:16) What Are Live Editor Tasks? What Are Live Editor Tasks?(0:55) Web サイトの選択
Control Flow Statements in R – Decision Making and Loops Data Visualization in R Basics of Data Structures with R Cheat Sheet Data Structures in R Programming Data Manipulation in R with Dplyr Package How to import data in R Programming? Variables and Data Types in R Programming Online R Comp...
Let’s apply the class() function to check thedata typesof our variables: sapply(data1,class)# Check classes of data frame columns# x1 x2 x3# "integer" "character" "character" The previous R code shows the class of each column, i.e. integer, character, and character. ...
mtry: Number of variables randomly sampled as candidates at each split.ntree: Number of trees to grow.mtry一般需要调参，ntree都是越大越好自己设定就行。在上面的过程中我们每棵树的节点都是不同的，叫做特征随机化，通过特征随机化我们保证了森林中树的多样性，随机森林模型也更加稳健。Feature randomness, ...
csv(csv_file_path) # check data uploaded print(DATA) #model preparation DATE = (DATA[,1]) head(DATA) summary(DATA) # choose length and variables Y<-DATA[c(0:nrow(DATA)),c(2:6)] #Rename variables (Norway_S = Southern Norway/ Norway_N = Northen Norway) colnames(Y) <- c("...