Machine Learning with CARET in R – Binary Classification with CARET in R CARET (short for “Classification And REgression Training”) is a powerful tool in R for training and comparing machine learning algorithms. One of the most common tasks in machine learning is binary classification, which is the process of sorting items into one of …
Classification in R – partial least squares discriminant in R Classification is a type of supervised machine learning that is used to predict the class or category of a new observation based on the values of its predictors. One popular method of classification is using partial least squares discriminant analysis (PLS-DA). PLS-DA is a technique …
Classification in R – naive bayes in R Classification is a type of supervised machine learning that is used to predict the class or category of a new observation based on the values of its predictors. One popular method of classification is using naive bayes algorithm. Naive Bayes is a probabilistic algorithm that is based …
Classification in R – logistic regression for multiclass classification in R Classification is a type of supervised machine learning that is used to predict the class or category of a new observation based on the values of its predictors. One popular method of classification is using logistic regression for multiclass classification. Multiclass classification is a …
Classification in R – logistic regression for binary class classification in R Classification is a type of supervised machine learning that is used to predict the class or category of a new observation based on the values of its predictors. One popular method of classification is using logistic regression for binary class classification. Logistic regression …
How to do Feature Selection – remove highly correlated features in R When working with a large dataset, it’s common to have features that are highly correlated with each other. These correlated features provide redundant information to the model and can negatively impact the performance. To overcome this issue, we can use feature selection techniques …
Data Cleaning in R – remove NULL values in R Data cleaning is an important step in the data analysis process, and one of the tasks is often identifying and removing NULL values. NULL values can occur for a variety of reasons, such as data entry errors or data being incomplete. These NULL values can …
Data Cleaning in R – remove duplicate values in R Data cleaning is an important step in the data analysis process, and one of the tasks is often identifying and removing duplicate values. Duplicate values can occur for a variety of reasons, such as data entry errors or data being collected multiple times. These duplicate …
Data Cleaning in R – mark missing values in R Data cleaning is an important step in the data analysis process, and one of the first tasks is often identifying and marking missing values. Missing values can occur for a variety of reasons, such as data entry errors or survey respondents not answering certain questions. …
Beginner’s Project on Regression in Python Machine learning regression is a type of machine learning where the goal is to predict a continuous value, such as a price or an age, based on a set of input features. It is used to model the relationship between a dependent variable and one or more independent variables. …