Abstract: Principal component analysis (PCA) stands as one of the most extensively utilized techniques in dimensionality reduction. However, PCA uses least squares (LS) loss which may yield poor ...
Abstract: The focus of this study is the processing and analysis of race data, and employs algorithms such as ARIMA model and Principal Component Analysis (PCA) to construct a series of data analysis ...
Unlike PCA (maximum variance) or ICA (maximum independence), ForeCA finds components that are maximally forecastable. This makes it ideal for time series analysis where prediction is often the primary ...
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