Ascent Science KNN plugin
Standard nearest-neighbor classification backed by sklearn.neighbors.KNeighborsClassifier.
python -m pip install ascent-science-knn==0.1.0
import ascent
model = ascent.machine_learning.KNNClassifier(n_neighbors=5, weights="distance")
model.fit(X, y)
predictions = model.predict(X_test)
Metadata
Release files for ascent-science-knn 0.1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| ascent_science_knn-0.1.0.tar.gz | 2.4 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| ascent_science_knn-0.1.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 5.2 kB
Release files / ascent_science_knn-0.1.0.tar.gz
| Download URL | ascent_science_knn-0.1.0.tar.gz |
|---|---|
| Size | 2.4 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
99e055b7d21329e5e351509b304682e8be932dace993746a602a39e787ebe7b0
|
|
BLAKE2b-256 checksum How to use checksums |
4e47006628f006aa8164af4b42660f854a867c57684bb0587333f744baa2c708
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.13.13
|
Release files / ascent_science_knn-0.1.0-py3-none-any.whl
| Download URL | ascent_science_knn-0.1.0-py3-none-any.whl |
|---|---|
| Size | 2.8 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
b02021ffba19bdfc1d4ff1b94110942ff21581c142a6d109497b9e347e0d8c15
|
|
BLAKE2b-256 checksum How to use checksums |
c42ef0d5846cbe70ba505dc034acede6bcda0bbcc92b2a0c4d47aabb93b108da
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.13.13
|