Difference between revisions of "...predict values"
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* ...rank ordered categories, then try the [[Ordinal Regression]] | * ...rank ordered categories, then try the [[Ordinal Regression]] | ||
* ...predict event counts, then try the [[Poisson Regression]] | * ...predict event counts, then try the [[Poisson Regression]] | ||
| − | * ...predict a distribution, then try the [[Fast Forest Quantile Regression]] | + | * ...predict a distribution with labeled data, then try the [[Fast Forest Quantile Regression]] |
* ...accuracy matters, I can NOT accept a long training time, and have little memory, then try a [[Decision Forest Regression]] | * ...accuracy matters, I can NOT accept a long training time, and have little memory, then try a [[Decision Forest Regression]] | ||
* ...accuracy matters, I can NOT accept a long training time, then try a [[Boosted Decision Tree Regression]] | * ...accuracy matters, I can NOT accept a long training time, then try a [[Boosted Decision Tree Regression]] | ||
* ...accuracy matters, I can accept a long training time, then try a [[Neural Network]] | * ...accuracy matters, I can accept a long training time, then try a [[Neural Network]] | ||
Revision as of 21:23, 31 May 2018
Regresssion The 5 Clustering Algorithms Data Scientists Need to Know
I want to...
- ...be fast, nice line fittings, then try the Linear Regression
- ...small dataset, nice line fittings, then try the Bayesian Linear Regression
- ...rank ordered categories, then try the Ordinal Regression
- ...predict event counts, then try the Poisson Regression
- ...predict a distribution with labeled data, then try the Fast Forest Quantile Regression
- ...accuracy matters, I can NOT accept a long training time, and have little memory, then try a Decision Forest Regression
- ...accuracy matters, I can NOT accept a long training time, then try a Boosted Decision Tree Regression
- ...accuracy matters, I can accept a long training time, then try a Neural Network
