Pre-release
This release is a pre-release and may not be stable for production use.
Visual ML is a library for visualizing the decision boundary of
machine learning models from Sklearn using 2D projections of pairs
of features. Here's an example:
```
>>> import visualml as vml
>>> import pandas as pd
>>> from sklearn.datasets import make_classification
>>> from sklearn.ensemble import RandomForestClassifier as RF
>>> # Create a toy classification dataset
>>> feature_names = ['A','B','C','D']
>>> X, y = make_classification(n_features=4, random_state=42)
>>> # The visualization is only supported if X is a pandas df
>>> X = pd.DataFrame(X, columns=feature_names)
>>> # Train a classifier
>>> clf = RF(random_state=42).fit(X,y)
>>> # Plot decision boundary grid
>>> vml.decision_boundary_grid(clf, X, y)
```
machine learning models from Sklearn using 2D projections of pairs
of features. Here's an example:
```
>>> import visualml as vml
>>> import pandas as pd
>>> from sklearn.datasets import make_classification
>>> from sklearn.ensemble import RandomForestClassifier as RF
>>> # Create a toy classification dataset
>>> feature_names = ['A','B','C','D']
>>> X, y = make_classification(n_features=4, random_state=42)
>>> # The visualization is only supported if X is a pandas df
>>> X = pd.DataFrame(X, columns=feature_names)
>>> # Train a classifier
>>> clf = RF(random_state=42).fit(X,y)
>>> # Plot decision boundary grid
>>> vml.decision_boundary_grid(clf, X, y)
```
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Release files for visualml 0.1b7
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| visualml-0.1b7.tar.gz | 12.2 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| visualml-0.1b7-py2-none-any.whl | Python 2 | none | any | Details |
Total release size: 19.8 kB
Release files / visualml-0.1b7.tar.gz
| Download URL | visualml-0.1b7.tar.gz |
|---|---|
| Size | 12.2 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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twine/1.11.0 pkginfo/1.3.2 requests/2.18.4 setuptools/39.0.1 requests-toolbelt/0.8.0 tqdm/4.23.0 CPython/2.7.12
|
Release files / visualml-0.1b7-py2-none-any.whl
| Download URL | visualml-0.1b7-py2-none-any.whl |
|---|---|
| Size | 7.6 kB |
| Tags | Python 2 |
|
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twine/1.11.0 pkginfo/1.3.2 requests/2.18.4 setuptools/39.0.1 requests-toolbelt/0.8.0 tqdm/4.23.0 CPython/2.7.12
|
