> For the complete documentation index, see [llms.txt](https://sisyphus.gitbook.io/project/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://sisyphus.gitbook.io/project/machine-learning/classification.md).

# Classification

### Logistic Regression

![](https://443921002-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-LGHUhl6VYqrZm4Re77O%2F-LURQrxWbJB-MlSBeUmt%2F-LUReCF1SXgTTWq60oll%2FScreen%20Shot%202018-12-23%20at%2012.00.45%20PM.png?alt=media\&token=adf9ed7d-5107-47dd-8232-4b47cf53fb4c)

![](https://443921002-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-LGHUhl6VYqrZm4Re77O%2F-LURQrxWbJB-MlSBeUmt%2F-LUReGweWlMDM7GAPdE-%2FScreen%20Shot%202018-12-23%20at%2012.01.24%20PM.png?alt=media\&token=488e1fd1-3776-405a-a55f-5e71d3b717cc)

![](https://443921002-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-LGHUhl6VYqrZm4Re77O%2F-LURQrxWbJB-MlSBeUmt%2F-LURezBiar88Ln2bmAYD%2FScreen%20Shot%202018-12-23%20at%2012.05.06%20PM.png?alt=media\&token=3febe96e-6eba-44fd-b9ee-6cdb32724bee)

Unfortunately, there is no closed-form solution for maximizing the log-likelihood (or minimizing the inverse, the logistic cost function); at least it has not been found, yet.

![](https://443921002-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-LGHUhl6VYqrZm4Re77O%2F-LURQrxWbJB-MlSBeUmt%2F-LUR_IWsa_UhkKpLUVWl%2Fimage.png?alt=media\&token=2c5901f0-6aeb-42dc-8803-1dbe4f9f8e03)

![](https://443921002-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-LGHUhl6VYqrZm4Re77O%2F-LURQrxWbJB-MlSBeUmt%2F-LURYJIEeFtBLQJWYHI7%2Fimage.png?alt=media\&token=e0070598-8273-4a67-8496-0bcbdeff3898)

### Neural Network Classification

[Log, Exp, Cross Entropy](https://sisyphus.gitbook.io/project/deep-learning-basics/basics/multi-class-and-cross-entropy-loss)

### SVM

Two class SVM 

![](https://443921002-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-LGHUhl6VYqrZm4Re77O%2F-LURQrxWbJB-MlSBeUmt%2F-LURVppwq15ZEKqDUl5f%2Fimage.png?alt=media\&token=4736d652-9f6b-45c0-aadb-596fa59d0b87)

[SVM Loss](https://sisyphus.gitbook.io/project/deep-learning-basics/basics/hinge-loss)

[Multi-class SVM vs. Cross Entropy](https://sisyphus.gitbook.io/project/deep-learning-basics/basics/multi-class-and-cross-entropy-loss)

[How to solve SVM](https://github.com/llSourcell/Classifying_Data_Using_a_Support_Vector_Machine/blob/master/support_vector_machine_lesson.ipynb)

### Decision Tree

### Random Forest

### GBDT

{% embed url="<https://www.coursera.org/lecture/python-machine-learning/gradient-boosted-decision-trees-emwn3>" %}

![](https://443921002-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-LGHUhl6VYqrZm4Re77O%2F-LUid5fGZQV8Rl9N-z2j%2F-LUilPhvBqQ20Pa0pftV%2FScreen%20Shot%202018-12-27%20at%2012.26.09%20AM.png?alt=media\&token=5842e658-5f84-4c9c-bc72-d3d758887719)

### Bayesian Network

### Nearest Neighbor Classification