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 lookup 6.5 Lazy evaluation 6.5.1 Promises 6.5.2 Default arguments 6.5.3 Missing argu...
rfeControl = rfeControl(functions = treebagFuncs)) 比较不同模型的性能 xyplot(lmProfile$results$RMSE + rfFuncs$results$RMSE + treebagFuncs$results$RMSE ~ lmProfile$results$Variables,ylab = "RMSE",xlab = "Variables", type = c("g", "p", "l"), auto.key = TRUE) xyplot(lmProfile$result...
If you are new to both R and Machine Learning Server, this tutorial introduces you to 25 (or so) commonly used R functions. In this tutorial, you learn how to load small data sets into R and perform simple computations. A key point to take away from this tutorial is t...
R has a special notation for describing relationships between variables. Suppose that you are assuming a linear model for a variable y, predicted from the variables x1, x2, ..., xn. (Statisticians usually refer to y as the dependent variable, and x1, x2, ..., xn as the independent va...
After you define all the variables and functions, the last line of code in the file initializes the SignalR connection by calling the SignalR start function. The start function executes asynchronously and returns a jQuery Deferred object. You can call the done function to specify the func...
There are two main functions that work in linear models - one for evaluating interactions between quantitative and qualitiative variables and one for evaluating interactions between two quantitative variables. Let’s look at the quantitative-qualitative interaction first. Prestige$income <- Prestige$...
You can interpret the first command as, “Store into an object named model the result of the lm (linear model) function analysis where the dependent variable to predict is the Rate column in the table object (data$Rate), and the independent predictor variables are Color...
11. What is the use of subset() and sample() functions in R? Subset() is used to select the variables and observations and sample() function is used to generate a random sample of the size n from a dataset. 12. Explain what is transpose. Transpose is used for reshaping of the data...
Variables Accuracy Kappa AccuracySD KappaSD Selected 1 0.8083 0.4702 0.03810 0.1157 * 2 0.8041 0.4612 0.03575 0.1099 3 0.8021 0.4569 0.04201 0.1240 4 0.7896 0.4378 0.03991 0.1249 5 0.7978 0.4577 0.04557 0.1348 6 0.7957 0.4471 0.04422 0.1315
The return statement is required if you want the function to save as variables the result or results following the operations in the function body. For example, if you want to create a function that calculates the mean of two numbers: mean_two_numbers <- function(num_1, num_2) { mean...