IRIS Flower Classification using SKLEARN DecisionTree Classifier with Grid Search Cross Validation The IRIS flower is a popular example in the field of machine learning. It is a type of flower that has different variations, such as the setosa, virginica, and versicolor. In this blog, we will be discussing how to classify the …
End-to-End Machine Learning: logloss metric in R When training a machine learning model, it’s important to evaluate its performance to understand how well it will work on new, unseen data. One common way to evaluate the performance of a model is by using a metric called “log loss” or “cross-entropy loss”. Log loss is a …
Support Vector Machine in R Support Vector Machine (SVM) is a type of supervised machine learning algorithm that can be used for both classification and regression tasks. It works by finding the best boundary, called a hyperplane, that separates different classes or predicts the target variable with the highest accuracy. In R, there are several …
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 …
How to do Feature Selection – recursive feature elimination in R Recursive feature elimination (RFE) is a feature selection technique that recursively removes the least important features from the dataset. The goal of RFE is to select a subset of features that are most informative and relevant to the target variable, while reducing the dimensionality …
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. …
Visualize Multivariate Data – Correlation plot in R A correlation plot is a useful tool for visualizing the relationship between multiple variables in a dataset. It allows to quickly identify patterns and trends in the data, and to determine whether variables are positively or negatively correlated. In R, there are different ways to create a …
Visualize Univariate Data – BOX plot in R In R, a box plot is a useful tool for visualizing univariate data, or data that has only one variable. A box plot is a graph that uses boxes to represent the distribution of the data and to identify any potential outliers. To create a box plot …
Summarise Data in R – How to know datatypes in R In R, it is important to know the data types of variables in a dataset, as different data types require different types of analysis and processing. The most common data types in R are numeric, character, and factor. To check the data types of …
Summarise Data in R – How to get summary statistics in R In R, summary statistics are a set of measures that provide a quick and easy way to understand the main characteristics of a dataset. These measures include measures of central tendency (such as mean and median) and measures of variability (such as standard …