GitHub / Honey28Git / Time-Series-Forecasting

Forecasting Wine Sales of Two Different types of Wine. After thorough Data Analysis, different models have been used and tested such as Exponential Smoothing Models, Regression, Naive Forecast, Simple Average, Moving Average. Stationarity of the data is checked. Automated Version of ARIMA/SARIMA Model built. Comparison of Models.

JSON API: http://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Honey28Git%2FTime-Series-Forecasting
PURL: pkg:github/Honey28Git/Time-Series-Forecasting

Topics: acf-pacf, arima-model, decomposition, exponential-smoothing-models, moving-average, naive-forecasting, prediction, regression-models, rmse-score, sarimax, simple-average, stationarity-test, time-series-analysis, wine-quality

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• Readme
• Dependencies