Data mining techniques and machine learning model for Walmart weekly sales forecast
Resumen
The ability to forecast data accurately
is extremely valuable in a vast array of domains
such as health, sales, finance, weather or sports.
Presented here is the study and implementation of
data mining techniques and ensemble regression
algorithm employed on sales data, consisting of
weekly retail sales numbers from different
departments in Walmart retail stores all over the
United States of America over the period of 3 years
with pre-holiday and holiday data presenting a
spike in sales. The model implemented for
prediction is Random. The metric to evaluate the
model was the Mean Absolute Error (MAE) value.
An analysis was performed to evaluate the model
and its ability to forecast accurately. It is also
notable that artificial neural networks can improve
the performance and achieve highly accurate
results.
Key Terms ⎯ Machine Learning, Mean
Absolute Error, Neural Networks, Random Forest,
Sales Forecasting.