Binary Cassification

Binary classification refers to those?classification tasks that have two class labels. Examples include: Email spam detection (spam or not). Churn prediction (churn or not)

A supervised learning approach called binary classification divides fresh data into one of two classifications.

Numerous techniques use binary categorization. The majority are:

Naive Bayes?

Naive Bayes methods are a set of supervised learning algorithms based on applying Bayes' theorem with the “naive” assumption of?conditional independence?between every pair of features given the value of the class variable.

Support Vector Machines

A support vector machine (SVM) is?a type of deep learning algorithm that performs supervised learning for classification or regression of data groups. In AI and machine learning, supervised learning systems provide both input and desired output data, which are labeled for classification.

Decision Trees with Nearest Neighbours

Logistic Regression

Logistic regression?estimates the probability of an event occurring, such as voted or didn't vote, based on a given dataset of independent variables.

Cognitive Networks

cognitive network (CN) is a new type of data network that makes use of cutting edge technology from several research areas (i.e. machine learning, knowledge representation, computer network, network management) to solve some problems current networks are faced with.