Pre-release
This release is a pre-release and may not be stable for production use.
MMKit: Multimodal Kit
A toolkit for multimodal information processing
Installation
pip install mmkit
An example
A Neural Network in PyTorch for Tabular Data with Categorical Embeddings. Here
from mmk.prediction import MultimodalPredictionModel
input_features=[ ... ]
categorical_features = [...]
output_feature = "..."
output_error=0
all_features=input_features+[output_feature]
mmpm=MultimodalPredictionModel("data/multimodal_data.csv",
all_features,
categorical_features,
output_feature,
output_error)
mmpm.train()
acc=mmpm.get_last_accuracy()
print(acc)
License
The mmkit project is provided by Donghua Chen.
1 maintainer
Metadata
1 maintainer
Release files for mmkit 0.0.1a0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| mmkit-0.0.1a0.tar.gz | 13.4 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| mmkit-0.0.1a0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 25.5 kB
Release files / mmkit-0.0.1a0.tar.gz
| Download URL | mmkit-0.0.1a0.tar.gz |
|---|---|
| Size | 13.4 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.27.1 requests-toolbelt/0.9.1 tqdm/4.31.1 CPython/3.6.6
|
Release files / mmkit-0.0.1a0-py3-none-any.whl
| Download URL | mmkit-0.0.1a0-py3-none-any.whl |
|---|---|
| Size | 12.1 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.27.1 requests-toolbelt/0.9.1 tqdm/4.31.1 CPython/3.6.6
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