Metadata-Version: 2.1
Name: embedding-tool
Version: 0.1
Summary: An embedding toolkit that can perform multiple embedding process which are low-dimensional embedding (dimension reduction), categorical variable embedding, and financial time-series embedding.
Home-page: https://github.com/thisisphume/embedding_tool/tree/master/
Author: Phume Ngampornsukswadi
Author-email: thisisphume@gmail.com
License: Apache Software License 2.0
Keywords: autoencoder PCA embedding
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Requires-Python: >=3.6
Description-Content-Type: text/markdown

# Dimension Reduction
> The function performs dimensionality reduction, pre-processing the data and comparing the reconstruction error via PCA and autoencoder.


## Install

`pip install embedding-tools`

## How to use

```python
from short_text_analyzer.core import *
```

**Input data:**
The input matrix has a size of 863 $\times$ 768.

```python
print ("Data's size: ", testing_data.shape)
print ("Dimension:   ", testing_data.shape[1])
```

    Data's size:  (863, 768)
    Dimension:    768


**Performing dimension reduction:** we will reduce the number of dimension from 768 to 2. 

```python
dim_reducer = dimensionReducer(analyzer.embeddingRaw, 2, 0.002)
dim_reducer.fit()
```


    ---------------------------------------------------------------------------

    NameError                                 Traceback (most recent call last)

    <ipython-input-5-6ee2cf251bab> in <module>
    ----> 1 dim_reducer = dimensionReducer(analyzer.embeddingRaw, 2, 0.002)
          2 dim_reducer.fit()


    NameError: name 'dimensionReducer' is not defined


**Calculating the MSE of the reconstructed vectors**

```python
dim_reducer.rmse_result
```


