In distributed learning, a model is trained via the collaboration of multiple workers. As a large amount of data is increasingly generated from mobile and edge devices (smart homes, mobile phones, wearable devices, etc.), it becomes essential for many applications to train machine learning models in parallel across many nodes. The power of machine learning lies in utilizing the growing size of training data as well as models so as to achieve high accuracy. Hello<- function (.Machine learning has achieved phenomenal breakthroughs in various fields, such as image recognition, language processing, gaming industry, product management, healthcare, etc. The most basic function is a function that has does not return any value. To remove particular vector from dataframe, simplify assume NULL to it. # 1 2 1 df #1st column # 2 4 df #2nd row, 1st column # 4 df <- ame(x=c(2,4),y=c(1,3))Ĭall particular elements in dataframe share the same syntax as in matrix or array. x <- c(2,4)Ī more compact code can be done by defining the vectors and the dataframe at the same time. One can first define vectors and then define dataframe based on the vectors. To skip having to rename the columns, we can simply specify the column name when creating the dataframe. We should give names to rows and columns to improve readability of the data. R will automatically name the column based on the elements inside that vector. Note that first rows are the columns names. Each spreadsheet is a dataframe – it is a collection of columns of cells. To visualize a dataframe, one may consider a standard Excel spreadsheet. ![]() It behaves like matrix but can contain strings (letters/words). ![]() Length(z) # 6 ncol(z) # 2 nrow(z) # 3ĭataframe is most useful form of data type in R. Size of matrix is rather complicated since it has two dimensions. One useful operation on matrix is to swap columns and row by t(), which means transpose. x #the second row # 5 6 7 8 x #the first column # 1 5 9 13 17 x #first row, second column # 2 x<- matrix(1:20, nrow=5, ncol=4, byrow=TRUE)Įxtracting elements from matrix is similar to extraction in vector. The following code fills the matrix by row. The following code fills the matrix by column. To define a matrix from a vector, the syntax is matrix(vector, nrow, ncol, byrow). However, in this case, we need to use the option include.lowest=TRUE to avoid data missing. Sometimes we may use quartile to cut instead. Sometimes we want to have label to avoid make it easier. The following divides data into three groups with the same length. While memory is usually not an issue these days, factor vector is sometimes converted from numeric vector to construct as categorical variable. It was created to save memory space because long strings converted to numbers, and only mapping is needed.Ī factor vector is created from character vector using factor(). Size of a vector can be found by using length() x <- 1:10Ī factor vector isan integer vector converted from character vectors or numeric vector. X #Pick out the 3rd element # 3.5 x #Pick out the first three elements # 1.0 -1.0 3.5 x #Pick out 1st, 3rd and 4th elements # 1.0 3.5 2.0 To get the first, third and forth elements, we use x. X + 2 #every element plus 2 # 3.0 1.0 5.5 4.0 x - 2 #every element minus 2 # -1.0 -3.0 1.5 0.0Įxtracting elements is using the operator. Since R is a vectorized program, applying mathematical operators to the vector will take effect on all elements inside the vector. It is easy to add new element to a vector. x <- c(1, -1, 3.5, 2)įinally, we create a generic character vector. We first create a generic integer vector. We input elements inside are separated by commas. To create a generic vector, we use the function c(). If the step is negative, then it is decreasing. Slightly more general way to create a vector of integer is to use seq().įor integers from 4 to 10 with each step being 2, we have ``seq(4,10,by=2)’’. ![]() This is usually a good way to initialize a vector. Sometimes, we want to repeat the same number several times. For a vector of integers from 1 to 5, we just need to use 1:5. The simplest vector is an integer vector. Vector is simply data of the same data type ordered in a list. Vector is the most common and basic data structure in R.
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