1 file was added to this release more than 14 days after its initial publication. Inspect the release files before installing.
baikal is a graph-based, functional API for building complex machine learning pipelines of objects that implement the scikit-learn API. It is mostly inspired on the excellent Keras API for Deep Learning, and borrows a few concepts from the TensorFlow framework and the (perhaps lesser known) graphkit package.
baikal aims to provide an API that allows to build complex, non-linear machine learning pipelines that looks like this:
with code that looks like this:
x1 = Input()
x2 = Input()
y_t = Input()
y1 = ExtraTreesClassifier()(x1, y_t)
y2 = RandomForestClassifier()(x2, y_t)
z = PowerTransformer()(x2)
z = PCA()(z)
y3 = LogisticRegression()(z, y_t)
stacked_features = Stack()([y1, y2, y3])
y = SVC()(stacked_features, y_t)
model = Model([x1, x2], y, y_t)baikal is compatible with Python >=3.5 and is distributed under the BSD 3-clause license.
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Release files for baikal 0.4.2
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Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| baikal-0.4.2.tar.gz | 32.2 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| baikal-0.4.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 67.0 kB
Release files / baikal-0.4.2.tar.gz
File added late
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While project maintainers occasionally add legitimate files to an existing release, late additions can also indicate a security compromise.
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| Download URL | baikal-0.4.2.tar.gz |
|---|---|
| Size | 32.2 kB |
| Tags | Source |
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twine/3.4.1 importlib_metadata/3.10.0 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.60.0 CPython/3.7.3
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Release files / baikal-0.4.2-py3-none-any.whl
| Download URL | baikal-0.4.2-py3-none-any.whl |
|---|---|
| Size | 34.9 kB |
| Tags | Python 3 |
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twine/3.2.0 pkginfo/1.6.1 requests/2.25.0 setuptools/40.8.0 requests-toolbelt/0.9.1 tqdm/4.51.0 CPython/3.7.3
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