34 potential prognostic factors were used in this analysis. Results Four classification trees (prognostic pathways or decision trees) were created, one for each outcome. The most important predictor ...

We propose a hierarchical differentiable neural regression model, Soft Decision Tree Regressor (SDTR). SDTR imitates a binary decision tree by a differentiable neural network and is plausible for ...

Then, Linear Regression, Decision Tree Regression and Artificial Neural Networks algorithms were analysed. It was revealed that decision tree regression is the more appropriate technique for this data ...

Here I propose a hybrid approach com- bining Long Short-Term Memory (LSTM) and Decision Tree Regression for stock prediction. The LSTM model captures sequential dependencies in stock time series data, ...

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