On the Use of <i>t</i>-Distributed Stochastic Neighbor Embedding for Data Visualization and Classification of Individuals with Parkinson’s Disease

<div>Parameter settings of the experiments. Note that for the preprocessing methods we explore all possible combinations between them (i.e., FS, IF, IA, FS-IF, FS-IA, IF-IA, and FS-IF-IA).</div>

Computational and Mathematical Methods in Medicine

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Figure 4

Figure 4: On the Use of <i>t</i>-Distributed Stochastic Neighbor Embedding for Data Visualization and Classification of Individuals with Parkinson’s Disease 

Figure 4 | On the Use of t-Distributed Stochastic Neighbor Embedding for Data Visualization and Classification of Individuals with Parkinson’s Disease 