Association Rule Learning Algorithm

Introduction to Association Rule Learning Association rule learning extracts alliances among the datapoints in a huge dataset. It incorporates the concept of data mining, which helps in finding useful commercial associations or regularities between the variables. It...

Hierarchical Clustering Algorithm

Introduction to Hierarchical Clustering The other unsupervised learning-based algorithm used to assemble unlabeled samples based on some similarity is the Hierarchical Clustering. There are two types of hierarchical clustering algorithm: 1. Agglomerative Hierarchical...

K-means clustering Algorithm

Introduction to K-means clustering K-mean clustering comes under the unsupervised based learning, is a process of splitting an unlabeled dataset into the clusters based on some similarity patterns present in the data. Given a set of m nos. of the data item with some...

Naïve Bayes Algorithm in Machine Learning

Introduction to Naïve Bayes Algorithm in Machine Learning The Naïve Bayes algorithm is a classification algorithm that is based on the Bayes Theorem, such that it assumes all the predictors are independent of each other. Basically, it is a probability-based machine...

Machine Learning Clustering Algorithm

Introduction to ML Clustering Algorithm Clustering falls under unsupervised learning methods. In this, the machine is provided with a set of unlabeled data, and the machine is required to extract the structure from the data from its own, without any external...

Machine Learning Classification Algorithm

Introduction to ML Classification Algorithm The process of guessing a category or a class from a given set of observations is known as Classification. The output can be categorized into “Yes” or “No” or “Red” or “Black.”...

Random Forest Algorithm for Machine Learning

Introduction to Random Forest Random forest is an ensemble-based supervised learning model. The concept of random forest is used in both classifications as well as in the regression problems. Basically, in ensemble-based learning, multiple algorithms are combined to...

Decision Trees in Machine Learning

Introduction to Decision Trees Decision trees are one of the most powerful classification algorithm that falls under supervised learning-based algorithms. It is used as a tool for making predictions and can be incorporated in different fields. With the help of...

Support Vector Machines

Introduction to SVM Support Vector Machines are part of the supervised learning model with an associated learning algorithm. It is the most powerful and flexible algorithm used for classification, regression, and detection of outliers. It is used in case of high...

Logistic Regression

The Logistic regression model is a supervised learning model which is used to forecast the possibility of a target variable. The dependent variable would have two classes, or we can say that it is binary coded as either 1 or 0, where 1 stands for the Yes and 0 stands...

Pin It on Pinterest