도움말 센터도움말 센터
Deep Learning Toolbox™를 사용하여 텍스트 분석과 계산 금융 응용 분야에 딥러닝을 적용합니다.
이 예제에서는 딥러닝 장단기 기억(LSTM) 신경망을 사용하여 텍스트 데이터를 분류하는 방법을 보여줍니다.
Classify text data that has multiple independent labels.
Convert decimal strings to Roman numerals using a recurrent sequence-to-sequence encoder-decoder model with attention.
Create, train, and compare three deep learning networks for predicting credit default probability.
Train a credit risk for probability of default (PD) prediction using a deep neural network. The example also shows how to use the locally interpretable model-agnostic explanations (LIME) and Shapley values interpretability techniques to understand the predictions of the model. In addition, the example analyzes model predictions for out-of-sample values and performs a stress-testing analysis.
Outperform the traditional BSM approach using an optimal option hedging policy.
다음 MATLAB 명령에 해당하는 링크를 클릭했습니다.
명령을 실행하려면 MATLAB 명령 창에 입력하십시오. 웹 브라우저는 MATLAB 명령을 지원하지 않습니다.
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