...predict values
Given a set of data points, we can use a clustering algorithm to classify each data point into a specific group. In theory, data points that are in the same group should have similar properties and/or features, while data points in different groups should have highly dissimilar properties and/or features. Clustering is a method of unsupervised learning and is a common technique for statistical data analysis used in many fields. We can use clustering analysis to gain some valuable insights from our data by seeing what groups the data points fall into when we apply a clustering algorithm. The 5 Clustering Algorithms Data Scientists Need to Know
I want to...
- ...be fast, nice line fittings, then try the Linear Regression algorithm
- ...rank ordered categories, then try the Ordinal Regression algorithm
- ...predict event counts, then try the Poisson Regression algorithm
- ...predict a distribution, then try the Fast Forest Quantile Regression algorithm
- ...accuracy matters, I can NOT accept a long training time, and have little memory, then try a Decision Forest Regression algorithm
- ...accuracy matters, I can NOT accept a long training time, then try a Boosted Decision Tree Regression algorithm
- ...accuracy matters, I can accept a long training time, then try a Neural Network
