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1.3.5 Heterogeneous Fusion

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The final property of data we need to present is whether all blocks in the data set are measured on the same scale or not, i.e., if the data set is homogeneous or heterogeneous. These concepts are explained in more detail in Chapter 2 (Section 2.2.2). Briefly, if all blocks contain measurements on the same scale, e.g., they are all numerical or quantitative data, then the resulting problem will be called homogeneous fusion. If they are not of the same scale, e.g., a mixture of quantitative and binary measurements, then the problem is called heterogeneous fusion. We will discuss both of these in this book although most methods are made for homogeneous data.

Multiblock Data Fusion in Statistics and Machine Learning

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