17.8 Machine Learning (Pro Only)

Machine-Learning

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 two types of tasks in machine learning, supervised learning and unsupervised learning.

• Supervised learning: Develop predictive models based on input data and allocate new observations to previously defined groups.
• Unsupervised learning： Interpret and group data based on input data. Classify observations or variables into groups.

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	Neural Networks Linear Regression (Simple, Polynomial, Multiple) Nonlinear Partial Least Squares GLM, GAM, GLMM, LME Bayesian Ridge Regression Quantile Regression Poisson Regression	K-Means Hierarchical Gaussian Mixture Optimal Cluster Number	PCA RDA ICA CCA Sparse PCA Factor Analysis nMDS