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使用 Deep Learning Toolbox™ 将深度学习融入文本分析和计算金融应用中。
此示例说明如何使用深度学习长短期记忆 (LSTM) 网络对文本数据进行分类。
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.
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