questions/data-science
Joining strings in R is quite an ...READ MORE
Logistic Regression often referred to as the ...READ MORE
Plotting multiple plots onto a single page ...READ MORE
Cross-validation is a model validation technique for ...READ MORE
Eigenvectors are used for understanding linear transformations. In data ...READ MORE
Univariate: These analyses are descriptive statistical analysis techniques which ...READ MORE
Sensitivity is commonly used to validate the ...READ MORE
Outlier values can be identified by using ...READ MORE
The extent of the missing values is ...READ MORE
In statistics and machine learning, one of ...READ MORE
Selection bias is the bias introduced by the ...READ MORE
The white noise (WN) model is a ...READ MORE
A random walk is a simple example ...READ MORE
Rattle is a popular GUI for data mining ...READ MORE
With the help of “plotly” we can ...READ MORE
You have to first create an object ...READ MORE
A confusion matrix can be used to ...READ MORE
You can use this command to create ...READ MORE
Consider this vector: a<-c(1,2,3,NA,4,5,NA,NA) Write the function to impute ...READ MORE
You can refer to the following packages ...READ MORE
Create data frame and then implement as ...READ MORE
You can assign a random ID to ...READ MORE
Why do'nt you try the dcast function, in the reshape2 package. d ...READ MORE
You can use something like this: df$grp.mean.values <- ...READ MORE
Just index back into the original data ...READ MORE
If you don't want to upgrade your ...READ MORE
If you convert 'y' to a factor, ...READ MORE
Classic hierarchical clustering approaches are O(n^3) in runtime and O(n^2) in ...READ MORE
Try the following code: sentence <- c("case sweden", ...READ MORE
K-means is based on variance minimization. The sum-of-variance formula ...READ MORE
You can try the following code: First, you ...READ MORE
Try the following code: data("Adult") rules <- apriori(Adult, ...READ MORE
I found out one solution: Use as() ...READ MORE
You can initially use kmeans, to calculate ...READ MORE
Here are the two main approaches. I ...READ MORE
Maybe this is what you want: # sample ...READ MORE
You can use repeat{} condition and check ...READ MORE
You can use this command droplevels() y <- ...READ MORE
Assuming that the data is in the ...READ MORE
Use reshape function: reshape(dat1, idvar = "name", timevar = ...READ MORE
read.csv () function is used to read ...READ MORE
If the programmers want the output to ...READ MORE
The eval() function evaluates an expression, but "5+5" is a string, ...READ MORE
Hi, You can use ? followed by the ...READ MORE
With dplyr 0.7.0, you can use pull to ...READ MORE
'dplyr' package provides 'summarise_all()' function to apply ...READ MORE
Run the below command in your Ubuntu/Linux ...READ MORE
R language has Homogeneous and Heterogeneous data ...READ MORE
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