wide_and_deep
Use wide and deep model to do multi-classification tasks.
This model is developed for the debt-collection robot. The robot calls customers within several topics. However, the human agents make different performances in these topics based on the payback money. If we find in a subtopic, human agents make a better performance, we will analyze the conversations they make with customers and write specific strategies for robots.
We collect the conversation between robot and customers and transform them into word2vector using a pre-trained model, use a bidirectional LSTM framework to extract features and use the wide and deep model to do the multi-label classification for higher accuracy (88-93%).
Install
pip install wide_and_deep
How to use
See demo https://jiaxiangbu.github.io/user_communication_classificationEX/
1 maintainer
Release files for wide-and-deep 1.0.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| wide_and_deep-1.0.0.tar.gz | 4.5 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| wide_and_deep-1.0.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 13.7 kB
Release files / wide_and_deep-1.0.0.tar.gz
| Download URL | wide_and_deep-1.0.0.tar.gz |
|---|---|
| Size | 4.5 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
4b403520ef82407c94a679e5e3f6aee2e0ecb9bbb7cef48a89c077cbeae4b554
|
|
BLAKE2b-256 checksum How to use checksums |
90dbc6176fd985ddaa6942c475b1215cbfccaf8542495f2e1018ed45b8a536c9
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.1.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/42.0.2 requests-toolbelt/0.9.1 tqdm/4.39.0 CPython/3.7.3
|
Release files / wide_and_deep-1.0.0-py3-none-any.whl
| Download URL | wide_and_deep-1.0.0-py3-none-any.whl |
|---|---|
| Size | 9.2 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
c6efc44cc126dffdd762edf387c24e284341c9c9d256b7b4b8affc6a9cc4f06c
|
|
BLAKE2b-256 checksum How to use checksums |
6e5db01ef8f747b5476e763471927a92b92e6339ba045a014e58590063910f6d
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.1.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/42.0.2 requests-toolbelt/0.9.1 tqdm/4.39.0 CPython/3.7.3
|
