fastML

A Python package built on sklearn for running a series of classification Algorithms on a given data in a faster and easier way.

Algorithms

Support Vector Machine

Decision Tree Classifier

Random Forest Classifier

K-Nearest Neighbors

Getting started

fork and clone this repo on your local machine and set-up your virtualenv by running the command

pip install -r requirements.txt

Installing the package

to install the package, navigate to the file directory and run:

pip install .

Usage

Assign the variables X and Y to the desired columns and assign the variable size to the desired test_size.

Ecoding Categorical Data

from fastML import EncodeCategorical
Y = EncodeCategorical(Y)

Check test.py to see the use case.

from fastML import fastML
size = <test_size goes here>
fastML(X, Y, size, RandonForestClassifier(), DecisionTreeClassifier(), KNeighborsClassifier(), SVC())

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Please make sure to update tests as appropriate.

License

MIT

ayoubGL/fastML