Metadata-Version: 2.1
Name: simple-kNN
Version: 1.1.0
Summary: Simple kNN algorithm with k-Fold Cross Validation
Home-page: https://github.com/chaitanyakasaraneni/simple-kNN
Author: Chaitanya Krishna Kasaraneni
Author-email: kc.kasaraneni@gmail.com
License: UNKNOWN
Description: # simple-kNN
        
        [![pypi](https://img.shields.io/pypi/v/simple-kNN?color=red&label=PyPI&style=for-the-badge)](https://pypi.python.org/pypi/simple-kNN)
        
        
        This repository is for Continuous Integration of my simple k-Nearest Neighbors (kNN) algorithm to pypi package.
        
        For notebook version please visit [this repository](https://github.com/chaitanyakasaraneni/knnFromScratch)
        
        #### *k*-Nearest Neighbors
        *k*-Nearest Neighbors, kNN for short, is a very simple but powerful technique used for making predictions. The principle behind kNN is to use **“most similar historical examples to the new data.”**
        
        #### *k*-Nearest Neighbors in 4 easy steps
         - Choose a value for *k*
         - Find the distance of the new point to each record of training data
         - Get the k-Nearest Neighbors
         - Making Predictions
           - For classification problem, the new data point belongs to the class that most of the neighbors belong to. 
           - For regression problem, the prediction can be average or weighted average of the label of k-Nearest Neighbors
        
        Finally, we evaluate the model using *k*-Fold Cross Validation technique
        
        #### *k*-Fold Cross Validation
        This technique involves randomly dividing the dataset into k-groups or folds of approximately equal size. The first fold is kept for testing and the model is trained on remaining k-1 folds.
        
        ## Installation
        ```
        pip install simple-kNN
        ```
        ## Usage
        
        ```
        from simple_kNN.distanceMetrics import distanceMetrics
        from simple_kNN.kFoldCV import kFoldCV
        from simple_kNN.kNNClassifier import kNNClassifier
        ```
        
        #### References
        - My [medium article on building kNN from scratch](https://link.medium.com/BV27Pox3qab)
        - More info on Cross Validation can be seen [here](https://medium.com/datadriveninvestor/k-fold-and-other-cross-validation-techniques-6c03a2563f1e)
        - [kNN](https://scikit-learn.org/stable/modules/generated/sklearn.neighbors.KNeighborsClassifier.html)
        - [kFold Cross Validation](https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.KFold.html)
        
Platform: UNKNOWN
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Intended Audience :: Science/Research
Requires-Python: >=3.6
Description-Content-Type: text/markdown
