k-NN
Algorithm
Overview
Use caseclassification and regression
Technical
Protocols
Integrates with
Knowledge graph stats
Claims13
Avg confidence91%
Avg freshness100%
Last updatedUpdated 2 days ago
WikidataQ319670
Trust distribution
100% unverified
Governance
Not assessed
k-NN
concept
k-nearest neighbors algorithm for finding closest points in vector space.
Compare with...primary use case
| Value | Trust | Confidence | Freshness | Sources |
|---|---|---|---|---|
| classification and regression | ○Unverified | High | Fresh | 1 |
| pattern recognition | ○Unverified | Moderate | Fresh | 1 |
integrates with
| Value | Trust | Confidence | Freshness | Sources |
|---|---|---|---|---|
| scikit-learn | ○Unverified | High | Fresh | 1 |
| NumPy | ○Unverified | Moderate | Fresh | 1 |
requires
| Value | Trust | Confidence | Freshness | Sources |
|---|---|---|---|---|
| distance metric | ○Unverified | High | Fresh | 1 |
| training dataset | ○Unverified | High | Fresh | 1 |
supports protocol
| Value | Trust | Confidence | Freshness | Sources |
|---|---|---|---|---|
| Euclidean distance | ○Unverified | High | Fresh | 1 |
| Manhattan distance | ○Unverified | High | Fresh | 1 |
based on
| Value | Trust | Confidence | Freshness | Sources |
|---|---|---|---|---|
| instance-based learning | ○Unverified | High | Fresh | 1 |
| feature similarity | ○Unverified | High | Fresh | 1 |
| lazy learning | ○Unverified | High | Fresh | 1 |
alternative to
| Value | Trust | Confidence | Freshness | Sources |
|---|---|---|---|---|
| decision trees | ○Unverified | Moderate | Fresh | 1 |