This chart was created to accompany a blog post which explores leveraging machine learning (RNN: LSTM) using Tensorflow Keras and SHAP to determine which factors (indicators and correlations with Macro, such as oil futures prices, Fed Funds rate, consumer spending, etc) are found by the model to be the most predictive in nature.
Findings will be posted in the comments.
This chart was created to accompany a blog post which explores leveraging machine learning (RNN: LSTM) using Tensorflow Keras and SHAP to determine which factors (indicators and correlations with Macro, such as oil futures prices, Fed Funds rate, consumer spending, etc) are found by the model to be the most predictive in nature.
Findings will be posted in the comments.
This chart was created to accompany a blog post which explores leveraging machine learning (RNN: LSTM) using Tensorflow Keras and SHAP to determine which factors (indicators and correlations with Macro, such as oil futures prices, Fed Funds rate, consumer spending, etc) are found by the model to be the most predictive in nature.
Findings will be posted in the comments.
