You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
12 lines
1.8 KiB
12 lines
1.8 KiB
# Explore classification methods
|
|
|
|
## Instructions
|
|
|
|
In [Scikit-Learn documentation](https://scikit-learn.org/stable/supervised_learning.html) you'll find a large list of ways to classify data. Do a little scavenger hunt in these docs: your goals is to look for classification methods and match a dataset in this curriculum, a question you can ask of it, and a technique of classification. Create a spreadsheet or table in a .doc file and explain how the dataset would work with the classification algorithm.
|
|
|
|
## Rubric
|
|
|
|
| Criteria | Exemplary | Adequate | Needs Improvement |
|
|
| -------- | ----------------------------------------------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------- |
|
|
| | a document is presented overviewing 5 algorithms alongside a classification technique. The overview is well-explained and detailed. | a document is presented overviewing 3 algorithms alongside a classification technique. The overview is well-explained and detailed. | a document is presented overviewing fewer than three algorithms alongside a classification technique and the overview is neither well-explained nor detailed. |
|