Skip to content

Latest commit

 

History

History
46 lines (32 loc) · 1.27 KB

README.md

File metadata and controls

46 lines (32 loc) · 1.27 KB
Raw

Trans4mers

Trans4mers is a sklearn compatible python package that implements some methods of data preprocessing. Currently the methods implemented are:

  • Imputation:
    • KNN Regression: This method imput values for missing values based on KNN Regression.
  • Feature Extraction: I'm not sure if the above methods are really feature extractors.
    • Hyberbolic Location Fingerprint: This method is used on Indoor Wifi Localization when there are heterogeneous devices environment. For more details: M. Kjaergaard and C. Munk, "Hyperbolic Location Fingerprint: A calibration-free solution for handling differences in signal strength", in PerCom, pp. 110-116, 2008
    • Relative Location Fingerprint: This method is just a variation of the above. Instead of use Hyberbolic tranformation it just take the relation betwee two variables.
  • Normalization:
    • Standard Normalization: This method normalize each row of a dataset based on the mean and standard variation among the variables of the row.

Instaling

First clone the repository to your machine:

git clone [email protected]:rloliveirajr/sklearn_transformers.git

Then, install the package using pip or easy_install:

pip setup.py install

Using

...

Contributions

Any contribution is welcome!