How to visualise Data in grey scale in R Visualizing data in gray scale can be useful in certain situations, such as when working with black and white printers or when you want to focus on the shape of the data rather than the color. In R, there are several ways to visualize data in …
How to visualise Data in multiple groups in R Visualizing data in multiple groups is a useful way to compare and contrast the characteristics of different groups of data. In R, there are several ways to visualize data in multiple groups, such as using side-by-side box plots, side-by-side bar plots, or small multiple plots. These …
How to utilize ggplot to visualise Data – scatter plots in R Visualizing data is an important step in understanding and interpreting the results of an analysis. One way to visualize data in R is by using the ggplot2 library, which is a powerful data visualization tool. One of the most common types of plots …
How to save trained model in R After training a model in R, it is often useful to save the model so that it can be used later without having to retrain it. R provides several ways to save a trained model, which include the save(), saveRDS(), and save() functions in the caret package. These …
How to do PCA in R to preprocess data Principal Component Analysis (PCA) is a technique used in data analysis to reduce the dimensionality of a dataset while retaining as much information as possible. In R, PCA can be used to preprocess data by transforming the original variables of a dataset into a new set …
How to preprocess data in R using Box-Cox Transformation Preprocessing data is an important step in any data analysis project. It involves cleaning and transforming the data so that it is ready for further analysis. One such transformation is the Box-Cox Transformation, which is used to normalize a dataset. In R, the Box-Cox Transformation can …
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How to pre-process data in R using scale method Pre-processing data is an important step in any data analysis project. It involves cleaning and transforming the data so that it is ready for further analysis. One common pre-processing technique is scaling, which is used to standardize the values in a dataset. In R, the scale …
How to utilise classification and regression tree model in R Classification and Regression Tree (CART) models are a popular method in the field of machine learning for both classification and regression tasks. In R, the “rpart” package is commonly used to build CART models. The first step in using a CART model is to prepare …
How to utilise CARET KNN Model in R K-Nearest Neighbors (KNN) is a type of supervised machine learning algorithm that is used for classification and regression. The caret package in R is a popular package for building machine learning models, and it also includes a KNN model. Here’s how to use the caret package to …