After the KNN-Classification I wanted to know which variables have the most relevance for the results. One approach for this is the Principal-Component-Analysis (PCA). It tries to create principal components (PC's) out of the variables so that less information gets lost. It is done here with the help of the sklearn-library.
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In this repository you find a python program and the prints and 3D-visualization of it. After the KNN-Classification I wanted to know which variables have the most relevance for the results. One approach for this is the Principal-Component-Analysis (PCA). More details in the python program as comments.
Baschin1103/Principal_component_analysis
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In this repository you find a python program and the prints and 3D-visualization of it. After the KNN-Classification I wanted to know which variables have the most relevance for the results. One approach for this is the Principal-Component-Analysis (PCA). More details in the python program as comments.
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