ThoKimHuynh / avocado_price_prediction

A variety of regression models (such as Random Forest, XGBoost, LightGBM) and time-series models (like Arima, Prophet, HoltWinters) are utilized to predict average price of avocados.

avocado_price_prediction

Business Objective:

Hass, a company based in Mexico, specializes in producing a variety of avocados for selling in U.S.A. They have been very successful over recent years and want to expand their business. Thus they want build a reasonable model to predict the average price of avocado “Hass” in the U.S.A to consider the expansion of existing avocado farms in other regions.

There are two types of avocados (conventional and organic) in the dataset and several different regions. This allows us to do analysis for either conventional or organic avocados in different regions and/or the entire United States.

Solutions:

There are 2 different approaches to solve this business objective:

First approach: create a regression model using supervised machine learning algorithms such as Linear Regression, Random Forest, XGB Regressor so on to predict average price of avocado in the USA.

Second approach: build a predictive model based on supervised time-series machine learning algorithms like Arima, Prophet, HoltWinters to predict average price of a particular avocado (organic or conventional) over time for a specific region in the USA.