Applied Data Science Coding with Python: SVM Algorithm The Support Vector Machine (SVM) algorithm is a method for classification and regression in machine learning. It is used to find the best boundary (or hyperplane) that separates different classes in the dataset with the greatest possible margin. The SVM algorithm starts by mapping the input data …
Applied Data Science Coding with Python: Naive Bayes Algorithm The Naive Bayes algorithm is a method for classification in machine learning. It is based on Bayes’ theorem which states that the probability of an event occurring is equal to the prior probability of the event multiplied by the likelihood of the event given certain evidence. …
Applied Data Science Coding with Python: LR Algorithm The Logistic Regression (LR) algorithm is a method for classification in machine learning. It is used to model the probability of a certain class or event occurring, given the values of certain features or inputs. The LR algorithm starts by finding the best set of coefficients that …
Applied Data Science Coding with Python: LDA Algorithm The Linear Discriminant Analysis (LDA) algorithm is a method for classification in machine learning. It is used to find a linear combination of features that separates different classes in the dataset with the greatest possible margin. The LDA algorithm starts by finding the mean vectors of the …
Applied Data Science Coding with Python: KNN Algorithm The K-Nearest Neighbors (KNN) algorithm is a method for classification and regression in machine learning. It is based on the idea that similar data points tend to have similar outcomes or labels. The KNN algorithm works by finding the K number of data points in the training …
Applied Data Science Coding with Python: CART Algorithm The CART (Classification and Regression Tree) algorithm is a powerful tool for both classification and regression problems in machine learning. It is used to create a decision tree that can be used to make predictions based on the input data. The CART algorithm works by recursively splitting …
How to get Regression Metric MAE Regression is a type of machine learning that is used to predict numerical values. One way to evaluate the performance of a regression model is to use a metric called Mean Absolute Error (MAE). To calculate MAE, you first need to have a dataset with both input variables (also …
Applied Data Science Coding with Python: How to get Classification Confusion Matrix A confusion matrix is a table that is often used to describe the performance of a classification model on a set of test data for which the true values are known. The matrix is used to visualize the model’s predictions and compare them …
Correlation Analysis in R – How to analyse and visualise correlated Data Correlation analysis is a statistical method that is used to examine the relationship between two or more variables. In R, there are several ways to perform correlation analysis, and one of them is by using the base R functions and packages such as …
How to utilise XGBoost : xgbLinear model in R XGBoost (eXtreme Gradient Boosting) is a powerful and widely-used machine learning algorithm, particularly in the field of gradient boosting. The xgbLinear model is a variation of XGBoost that is particularly well suited for linear problems. In R, the “xgboost” package can be used to build and …