17.8 Machine Learning (Pro Only)

Introduction

Machine learning is a method of data analysis that learns information directly from data to automate analytical model building. The machine learning algorithms learn from data, identify patterns and make decisions.

There are three types of tasks in machine learning: supervised learning, unsupervised learning, and data reduction.

• Supervised learning: Develop predictive models based on input data and assign new observations to previously defined groups or predict their response values.
• Unsupervised learning: Analyze and group data based on input data without predefined groups. It can be used to classify observations or variables into groups and identify underlying patterns.
• Data reduction: Reduce the dimensionality or complexity of data while preserving the most important information, making the data easier to analyze and visualize.

Tools of Machine Learning in Origin

Origin provides various tools of machine learning to help you investigate your data

Classification	Regression	Clustering	Data Reduction
Decision Tree Analysis Neural Networks SVM Logistic Regression Discriminant Analysis PLS-DA Random Forest	Neural Networks Linear Regression (Simple, Polynomial, Multiple) Nonlinear Partial Least Squares GLM, GAM, GLMM, LME Bayesian Ridge Regression Quantile Regression Poisson Regression Decision Tree Analysis Random Forest	K-Means Hierarchical Gaussian Mixture Optimal Cluster Number	PCA RDA ICA CCA Sparse PCA Factor Analysis nMDS