Metadata-Version: 2.1
Name: sklearn-ts
Version: 0.0.1
Summary: Package for time series forecasting
Home-page: https://github.com/lady-pandas/sklearn-ts
Author: Marta Markiewicz
Author-email: m.markiewicz.pl@gmail.com
License: MIT
Description: # Welcome to sklearn-ts
        
        Testing time series forecasting models made easy :)
        This package leverages [scikit-learn](https://github.com/scikit-learn/scikit-learn), simply tuning it where needed for time series specific purposes.
        
        Main features include:
        - Moving window time split
            - train-test split
            - CV on moving window time splits
        - Model wrappers:
            - Neural networks
            
        Other python packages in the time series domain:
        - [sktime](https://github.com/alan-turing-institute/sktime)
        - [sktime-dl](https://github.com/sktime/sktime-dl)
        - [darts](https://github.com/unit8co/darts)
        
        # Installation
        
        ```bash
        pip install sklearn-ts
        ```
        
        # Quickstart
        ## Forecasting COVID-19 with Linear Regression
        ```python
        from sklearn_ts.datasets.covid import load_covid
        from sklearn.linear_model import LinearRegression
        from sklearn_ts.validator import check_model
        
        dataset = load_covid()['dataset']
        dataset['month'] = dataset['date'].dt.month
        
        params = {'fit_intercept': [False, True]}
        regressor = LinearRegression()
        
        results = check_model(
            regressor, params, dataset,
            target='new_cases', features=['month'], categorical_features=[], user_transformers=[],
            h=14, n_splits=2, gap=14,
            plotting=True
        )
        ```
        
        ![alt text](tests\LinearRegression.png)
        
        # Forecasting models
        
        | Model family | Model | Univariate |
        | ------------- |:-------------:| -----:|
        | Neural networks | ANN | 1 |
        | Neural networks | LSTM | 1 |
        | Neural networks | TCN | 1 |
        
        # Documentation
        Tutorial notebook preparation in progress.
        
        # Development roadmap
        - New repo
        - Remove old deploy from test
        - Pypi
        - Exploding MAPE
        - Handling many observations per date
        - Constant window for forecasting
        - Tutorial notebooks
        - image not included
Keywords: time series forecasting deep learning machine learning regression ARIMA ETS
Platform: UNKNOWN
Description-Content-Type: text/markdown
