Dataconomy

MARCH 17, 2025

Unsupervised models Unsupervised models typically use traditional statistical methods such as logistic regression, time series analysis, and decision trees. These methods analyze data without pre-labeled outcomes, focusing on discovering patterns and relationships.

Decision Trees 91

Decision Trees Predictive Analytics Data Preparation Machine Learning 91

IBM Journey to AI blog

DECEMBER 20, 2023

And retailers frequently leverage data from chatbots and virtual assistants, in concert with ML and natural language processing (NLP) technology, to automate users’ shopping experiences. Classification algorithms include logistic regression, k-nearest neighbors and support vector machines (SVMs), among others.

Machine Learning 92

Machine Learning Machine Learning Supervised Learning Clustering 92

Dataconomy

AUGUST 31, 2023

Here are some examples of where classification can be used in machine learning: Image recognition : Classification can be used to identify objects within images. The goal of unsupervised learning is to identify structures in the data, such as clusters, dimensions, or anomalies, without prior knowledge of the expected output.

Machine Learning 136

Machine Learning Machine Learning Supervised Learning Algorithm 136