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Time Series of Price Anomaly Detection with LSTM

#artificialintelligenceSep-10-2020, 10:25:49 GMT

Autoencoders are an unsupervised learning technique, although they are trained using supervised learning methods. The goal is to minimize reconstruction error based on a loss function, such as the mean squared error. In this post, we will try to detect anomalies in the Johnson & Johnson's historical stock price time series data with an LSTM autoencoder. The data can be downloaded from Yahoo Finance. The time period I selected was from 1985–09–04 to 2020–09–03.

artificial intelligence, machine learning, price anomaly detection, (4 more...)

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