Posts with the tag: Time Series

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Heart Illness Classification AutoEncoders

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Heart Illness Classification AutoEncoders In this project, you will work with LSTM-based autoencoders to classify human heart beats for heart disease diagnosis. The dataset contains 5,000 Time Series examples with 140 timesteps. Each time-series is an ECG or EKG signal that corresponds to a single heartbeat from a single patient with congestive heart failure. An electrocardiogram (ECG or EKG) is a test that checks how your heart is functioning by measuring the electrical activity of the heart.

Time-Series SARIMAX

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Time-Series SARIMAX I analyzed Autocorrelation Functions (ACF) & Partial Autocorrelation Functions (PACF) to determine the ARIMA models' order. Additionally, I conducted necessary differencing to preprocess the data into the stationary assumption. In addition to appraisal processing, I conducted a graph brute force search to identify the best model order with the smallest AIC & BIC metrics. Lastly, I executed a predictive analysis with 95% confidence to forecast the succeeding year’s revenue.