Diy Platform App Store Index Price Forcasting
Price Forecasting is a statistical measurement(type of a regression problem) that attempts to predict a commodity/product/service price by evaluating various factors/events(known as independent variables in data set), which responsible for changing price in the market.
How to Build your Price Forecasting application
For Price Forecasting data preparation steps visit here
We have provided a sample data set, which contains 9 different attributes or features and target label namely Amount_Per_Room_Night. The value of target label is price per night of the room on given date.
- Go to the app store, build a lead score app by searching for Price Forecasting
- You will be redirected to the app settings page where you can configure and run the app
- Under Quick Settings,
3.1. Select an existing dataset or upload a new dataset.
3.2. Select the target field, the field that indicates the demand.
- Now click on Run Now to start the app. The app may run for 5 to 20 minutes (dependending on the size of input data) and then the trained model will be saved.
- Use this model to get the price prediction
5.1. Click on Build App on the model to build the inference app using that model
5.2. Provide the input in the given fields and click on Get Results. The predicted price of room will be displayed on the right side of the screen.
- [Optional] To use this model to predict more than one examples, [Visit here] [TODO]
The output of the infer app will the predicted value of your example.
Go ahead and build your first Price Forecasting App