Difference between revisions of "Machine Learning"
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| Line 2: | Line 2: | ||
* Supervised Learning | * Supervised Learning | ||
| − | ** Regression Problem: Continuous valued output | + | ** Regression Problem: Continuous valued output. |
| − | ** Classification Problem: Discrete valued output | + | ** Classification Problem: Discrete valued output. |
* Unsupervised Learning | * Unsupervised Learning | ||
** Clustering | ** Clustering | ||
Revision as of 23:21, 19 October 2014
Types of Machine Learning
- Supervised Learning
- Regression Problem: Continuous valued output.
- Classification Problem: Discrete valued output.
- Unsupervised Learning
- Clustering
Linear Regression
Classification Problem
$\log yh_\theta(x) + (1-y) \log (1-h_\theta(x))$ comes from Maximum Likelihood Method in Statistics