Use Regression Forest to predict stock prices.

[Instructions]

1. stock_regression_forest_1_preparation.ipynb

Set the parameters:

• input_data: input data file path

• input_augmentation: the amount of data augmentation

• predicted_output: predict the stock price in a few days

• validation_proportion: the proportion of the validation data

After the setting is completed, it can be executed.

2. stock_regression_forest_2_train.ipynb

Set the parameters:

• num1: the number of data amplification

• num2: predict the stock price in a few days

After the setting is completed, it can be executed.

3. stock_regression_forest_3_inference.ipynb

Set the parameters:

• num1: the number of data amplification

• num2: predict the stock price in a few days

After the setting is completed, it can be executed.

After execution, you can see the results of Regression Forest inference.

Data-Regression-Forest-Stock-inference-Jupyter.png

This SDK is built in AppForAI - AI Dev Tools.

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